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• Published: 05 July 2022

A meta-review of psychological resilience during COVID-19

• Katie Seaborn   ORCID: orcid.org/0000-0002-7812-9096 1 ,
• Kailyn Henderson 2 ,
• Jacek Gwizdka   ORCID: orcid.org/0000-0003-2273-3996 3 &
• Mark Chignell   ORCID: orcid.org/0000-0001-8120-6905 2  

npj Mental Health Research volume  1 , Article number:  5 ( 2022 ) Cite this article

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Psychological resilience has emerged as a key factor in mental health during the global COVID-19 pandemic. However, no work to date has synthesised findings across review work or assessed the reliability of findings based on review work quality, so as to inform public health policy. We thus conducted a meta-review on all types of review work from the start of the pandemic (January 2020) until the last search date (June 2021). Of an initial 281 papers, 30 were included for review characteristic reporting and 15 were of sufficient review quality for further inclusion in strategy analyses. High-level strategies were identified at the individual, community, organisational, and governmental levels. Several specific training and/or intervention programmes were also identified. However, the quality of findings was insufficient for drawing conclusions. A major gap between measuring the psychological resilience of populations and evaluating the effectiveness of strategies for those populations was revealed. More empirical work, especially randomised controlled trials with diverse populations and rigorous analyses, is strongly recommended for future research.

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Introduction.

The COVID-19 pandemic has disrupted many aspects of life at a global scale. Mental health and psychological well-being have subsequently emerged as key research foci in healthcare and public health during the pandemic 1 , 2 , 3 , 4 . Most countries have endorsed interventions with known or foreseen effects on psychological well-being, such as social distancing, physical isolation, and self-quarantine. Given what is already known about the relationship between mental health and psychological interventions 5 , this has further motivated questions on the assessment, management, and prevention of negative psychological outcomes 1 , 2 , 3 , 6 , 7 , 8 . Psychological resilience plays an essential role in times of crisis. As a behavioural characteristic, it can be framed as positive adaptability: the ability to “bounce back” when confronted with unusual and negative circumstances involving adversity, stress, and trauma 9 , 10 . Psychological resilience may be affected by socio-economic status 11 , cultural factors 12 , and other sources of influence. In pandemics, psychological resilience may dramatically affect outcomes. External offerings, such as social support systems, may reduce levels of depression 1 , while internal orientations related to psychological stress 2 , coping skills 2 , positive mood 7 , and positivity, especially “finding the good in the bad,” 9 are all facets of psychological resilience that subdue or prevent negative outcomes. The extent to which it is achieved, and how, may be a fundamental determinant of a population’s ability to combat mental health difficulties resulting from stressors related to the COVID-19 global pandemic.

A meta-review is a standard way of assessing the state of affairs. Meta-reviews, also termed umbrella reviews or overviews of reviews, are systematic reviews of extant review work that aim to achieve clarity and consensus on a specific research question or topic while considering factors such as review quality and bias 13 , 14 . Intended beneficiaries are decision-makers, the academic community, and the public. Meta-reviews synthesise systematic reviews and meta-analyses of primary studies, which typically represent the highest achievable level of evidence 13 . As such, assessing the quality of the body of review work is a key component of meta-reviews 13 . However, the COVID-19 pandemic has resulted in a unique set of circumstances. Indeed, the ongoing, pressing need for answers has led to a large number of submitted manuscripts, as well as greater leniency in publishing criteria 15 . Emerging from this “paperdemic” are crucial questions regarding scientific integrity during COVID-19 15 . The collection of review work on psychological resilience may be subject to the same pressures of time and demand. Yet, as indicated by citation counts and media coverage, this work is being relied upon to inform our understanding of the situation and make public health decisions. A rigorous evaluation is necessary to reach consensus for healthcare governance and identify current inadequacies that must be accounted for in future editorial policies and publishing requirements.

This meta-review addresses an urgent need to both assess what is known about psychological resilience during COVID-19 and appraise the quality of research and review work being conducted on this topic. Our research objectives were: (RQ1) to summarise the nature and quality of this body of work and (RQ2) to derive a consensus on strategies implemented to evaluate, maintain, and cultivate psychological resilience throughout the COVID-19 pandemic. While our objective was to provide a reliable overview of the review work along with the means for building knowledge and taking action, we were largely limited by the state of the literature. In short, we cannot offer strong evidence for or against the strategies gathered across the corpus of survey work. Indeed, the severe limitations in this body of work are alarming and undermine the recommendations offered by specific reviews, however highly cited. We map out a series of psychological resilience factors, measures, and strategies gathered from these reviews that, while having potential validity, urgently need high quality empirical work on their efficacy within the context of the COVID-19 pandemic.

Review sample and characteristics

From an initial total of 281 reviews retrieved across three databases in two phases, 97 were screened and 30 were selected for analysis (Fig. 1 ). Excluded reviews and reasons for their exclusion are presented in Supplementary Table 4 .

PRISMA flow chart showing study inclusion and exclusion at the identification, screening, and included stages. The identification stage featured an initial search of two databases and a main search of three databases. The screening stage involved screening records, retrieving reports, and assessing their eligibility. Of these, 30 were included in the final stage.

General characteristics of the included reviews are presented in Supplementary Table 5 . Study characteristics were extracted from the 30 included reviews, all of which were published in 2020 or 2021. The review types included narrative (7), rapid (8), systematic (2), scoping (4), mini (1), and mixed methods (1). Only ten (33%) reviews used protocols: four pre-registered with PROSPERO, two with OSF (one in parallel), one with Cochrane Reviews, and three available but unregistered. Of these, one was available from the authors upon request, one was uploaded to an institutional website, and one explained “any discrepancies from the study as planned (and, if relevant, registered)” 11 , 16 . Three reviews were highly cited (50 or more citations) but had no registered protocol and were deemed of low quality; three had registered protocols and were highly cited but of low quality; and five highly cited reviews, deemed of sufficient quality, had no registered protocol.

Participants were from the general population (all ages), as well as subset populations such as individuals working in healthcare (e.g., nurses, doctors, medical staff, social workers, etc.). Specific settings included hospitals, clinics, medical centres, and workplaces. Specific contexts mostly pertained to specific outbreak and pandemic situations, such as SARS, COVID-19, Ebola, H1N1, and MERS (Table 1 ). Twenty-five (83%) studies reported the number of databases searched, which ranged between 1 and 14 (M = 4.84, SD = 2.56, MD = 4, IQR = 3), with the earliest search being carried out on November 17, 2019, and the latest search on March 15, 2021. Twenty-three reviews (77%) reported the number of studies included, which ranged from 2 to 139 (M = 36.65, SD = 32.09, MD = 25, IQR = 31). These included qualitative and quantitative study designs: cross-sectional (surveys, observational), longitudinal, randomised controlled trials (RCTs), descriptive, cohort (prospective, retrospective), interviews, reviews, case-control, and mixed-methods. These studies were conducted in and across six continents: Asia, Africa, North America, South America, Europe, and Australia. Frequent countries of origin of the studies included China, UK, USA, Canada, India, Hong Kong, Italy, and Taiwan. Many of the outcomes reported pertained to the psychological and mental health impacts, e.g., anxiety, stress, depression, posttraumatic stress disorder (PTSD), insomnia, of COVID-19, and risk factors for these impacts.

Risk of bias across reviews

Full details of the risk of bias assessments are presented in Table 2 . The mean SANRA scores for qualitative reviews was 0.74 (SD = 0.12) and the mean JBI score for all other reviews was 0.78 (SD = 0.21). Based on the cut-off of 0.8, 15 reviews were determined to be of sufficient quality to answer RQ2: psychological resilience strategies.

Measures of psychological resilience

Reviews provided 31 unique positive measures (Table 3 ) and 55 unique negative measures (Table 4 ) to assess individuals’ psychological resilience status. Most also covered risk (with respect to negative measures) and protective (with respect to positive measures) factors and status results. A total of 14 risk factors (Table 5 ) and 7 protective factors (Table 6 ) were identified. Half of the factors received a GRADE score of moderate (7/14 for risk factors and 3/7 for protective factors). Counterpoints were included where possible to highlight patterns in how factors were framed and indicate where gaps and possibilities exist.

Strategies for psychological resilience

A corpus of 19 high-level strategies were gathered (Table 7 ). Most (17/19 or 89%) could not be given a GRADE score due to insufficient evidence, and the two remaining received very low GRADE scores. A further 15 specific training and/or intervention programmes were identified. Most were only identified by one review. The programmes were: Psychological first aid (PFA) 17 , 18 , 19 , trauma risk management (TRiM) 17 , 18 , eye movement desensitisation and reprocessing (EMDR) 17 , 18 , cognitive behavioural therapy (CBT) 18 , 20 , 21 , cognitive behavioural therapy for insomnia (CBTi) 18 mindfulness-based cognitive therapy (MBCT) 21 , mindfulness-based stress reduction (MBSR) 18 , occupation therapy (OT) 18 , Motivational Interviewing (MI) 20 , resilience and coping for the healthcare community (RCHC) 17 , anticipate, plan, and deter (APD) 17 , resilience at work (RAW) 17 , mindfulness training 19 , 21 , 22 , 23 , hardiness training 21 , 22 , and crisis intervention 20 .

Almost none of the high-level strategies or specific programmes were evaluated for their effectiveness, within or outside of COVID-19. Moreover, only one review 24 focused on longitudinal work, while also including and merging together non-longitudinal work, such as naturalistic studies. Indeed, 8 of the 15 reviews (53%) called for longitudinal research as future work. One exception was a significant effect of the number of protective measures and equipment provided within work contexts on reducing psychological distress, according to the reporting of Giorgi et al. 20 on 6 of 42 papers. However, no risk of bias or quality assessment was conducted, limiting our ability to draw conclusions on the strength or generalisability of this strategy. The other exception was PFA. Pollock and colleagues 18 reported on a cluster-randomised study by Sijbrandij et al. 25 in which PFA was evaluated through a measure of burnout against a control (no intervention) at baseline, post-assessment, and follow-up stages with 408 participants. Results for completers and intention-to-treat groups indicated that there was no significant difference between groups or over time (95% CI). However, Pollock et al. noted risk of bias due to insufficient reporting, use of single items from a multi-item measure, and weak statistical analyses. Subsequently, we are not confident that there is sufficient evidence to draw conclusions about the efficacy of PFA. Indeed, we are not confident to recommend any of these high-level strategies or specific programmes, based on the review work so far.

Review work, especially systematic surveys, are considered the gold standard of evidence 13 . A wide range of professionals rely on review syntheses to make decisions on policy, practice, and research 26 . In global pandemics, psychological health and resilience are key variables that impact the ability of individuals and populations to recover and carry on. As such, recognition of resilience factors, methods of measuring resilience, and strategies to build and maintain resilience are essential. Unfortunately, this meta-review indicates that the present body of review work is severely limited, leaving us unable to confidently summarise or synthesise knowledge for public health. The implications are grave, particularly given that some of this research has already been used to inform decision-making and justify subsequent research. Additionally, it is difficult to advocate for or against measures and guidance in terms of clinical practice.

Assessing review quality is one of the main objectives of meta-review work 13 . The quality of this corpus was very low overall. Furthermore, a large portion of the work could not be assessed due to insufficiency in reporting and weaknesses in review methodology. The intended main target—strategies for psychological resilience—was particularly impacted. The narrative reviews were notably biased, characterised by opinions and claims without literature backing or reasoning. The quality of most of these reviews was subsequently too low to meet the standard for inclusion in our analyses. The other types of reviews were also insufficient to draw conclusions. Meta-analyses were not possible due to the sheer variety of measures (i.e., heterogeneity) and disconnect between these measures and the strategies reported. Indeed, we found a preponderance of instruments for a relatively short list of measures, with little reasoning behind this diversity. Moreover, most of the strategies reported were mere suggestions rather than options grounded in evidence-based sources. The two strategies that did have some evidentiary support—namely, providing PPE and training or intervention programmes—were nevertheless deemed by ourselves and the original reviewers as very low in quality. In short, we have found clear and widespread evidence that the review work on psychological resilience has been subject to the COVID-19 “paperdemic” phenomenon 15 . This leaves us unable to provide recommendations with confidence. Yet, some of these reviews, notably Preti et al. 27 ( c  = 269), Etkind et al. 28 ( c  = 171), and Heath et al. 29 ( c  = 128), have received a lot of attention via citations, news outlets, and social media. In light of their quality, reliance on these papers to inform policy and practice is inadvisable. At best, these reviews signal a keen interest and urgent need for rigorous, empirical work on matters pertaining to psychological resilience.

Synthesising the nature of the review work revealed several biases and gaps. Most of the reviews were focused on frontline healthcare workers (HCWs) and women. Yet, the literature points to several other groups for whom psychological resilience and/or well-being may be integral within the context of COVID-19, including older adults 30 , people with disabilities 31 , LGBTQ + folk 32 , people with pre-existing mental health conditions 7 , 30 , racialized groups and ethnic minorities 33 , 34 , and people living in low-income and/or isolated areas 35 . A certain level of bias in focus is a natural and common feature of many areas of study 36 . Yet, it cannot be allowed to influence review work, once discovered. We encourage researchers and practitioners to consider work focused on these overlooked populations. Additionally, the way that psychological resilience has been approached needs reconsideration. We found a negative bias in factors and measures. Most measures defined resilience as the absence of mental health problems rather than the presence of fortitude, flexibility, growth, and so on. We also found a concerted focus on risk, rather than protective, factors. While identifying who may be more susceptible and in what contexts is important, it is equally important to determine what characteristics and conditions are favourable to higher rates of psychological resilience. Mental health and well-being stressors may be unavoidable in a pandemic, which this negative bias highlights. Yet, without knowledge of additive and protective factors, it is difficult to make suggestions for clinical practice. Our tables highlight these gaps and can be used to guide future research. Finally, the gap between psychological resilience measures and strategies needs to be addressed, with strategies assessed via these measures in longitudinal studies within the context of COVID-19. Clinical practice and public health would be well-served by a direct link between negative or positive outcomes and the various strategies offered. Without this work and the consensus that a review of it could offer, we cannot make recommendations with confidence.

Methodologically, there was some consistency in the limitations observed in the surveyed review work. Most reviews were not associated with a registered protocol, such as on PROSPERO or Covidence. This created undue repetition in the corpus. It is strongly encouraged that all review protocols be registered in advance; with a hot topic like COVID-19, it is likely that review work is already being undertaken. Additionally, most works included research conducted outside of the COVID-19 pandemic and did not distinguish which results were particular to COVID-19. As such, we cannot draw conclusions on whether there are any special features of the COVID-19 context relevant to psychological resilience. Future work should focus on research conducted during COVID-19 or should delineate between studies conducted during COVID-19 and other contexts, including other pandemics.

This meta-review is limited in a few ways. The heterogeneity in the corpus made it difficult to find and extract data for synthesis and comparison. For example, some reviews reported on sample size in terms of the number of people, while others reported on the number of hospitals or used another population metric. Additionally, finding a “one size fits all” tool for quality and risk of bias assessment proved challenging. This may be a matter of the topic (i.e., a feature of work on psychological resilience) or the breadth of review types included. As with most meta-reviews, included reviews sometimes reported on the same studies, and so certain characteristics that appear to be common across reviews may actually reflect multiple citations of the same study. This issue also limits the accuracy of estimating the number of studies (aggregated across the reviews) that were surveyed. While it is beyond the scope of the present work, this may be addressed by extracting the studies from all reviews, eliminating duplicates, and re-conducting the analyses for each review—a significant effort that may not yield findings equivalent in value to the time and labour required.

The original search was conducted in June 2021, and more reviews are likely to have been published since that time. A retrospective covering the “last waves” of the pandemic will be a necessary future complement to the present meta-review. In the meantime, we briefly comment on a few relevant papers that speak to the issue of longitudinal changes during the pandemic. Riehm et al. 37 noted that time as a factor of resilience is severely understudied. Their findings from over 6000 adults in the Understanding America Study showed that mental distress varied markedly by resilience level during the early months of the COVID-19 pandemic, with low-resilience adults reporting the largest increases in mental distress. Bäuerle et al 38 . evaluated the impact of the “CoPE It” e-mental health intervention designed to improve resilience to mental distress during the pandemic. However, while they found a significant net gain between baseline and post-intervention, they relied on data obtained at only two time points and did not use a control group. There remains an urgent need for longitudinal studies of the effectiveness of interventions to increase psychological resilience during pandemics. A recently published study protocol by Godara et al. 39 exemplifies the type of research that is needed in this area. The planned study on a mindfulness intervention would last ten weeks, involve 300 participants, include a control group, and cover a range of key outcomes, such as levels of stress, loneliness, depression and anxiety, resilience, prosocial behaviour, empathy, and compassion. This proposed study and others like it could provide the needed information on the effectiveness of interventions to improve psychological resilience that is currently lacking.

We conclude with a sober reflection on the state of affairs. As this meta-review has shown, there is insufficient high-quality evidence to inform policy and practice. The silver lining is that a way forward can be mapped through the gaps and weaknesses that characterise this body of work. We urgently recommend the following:

Systematic reviews that follow international standards for methodology (e.g., Cochrane, JBI) and register their protocol through PROSPERO or an equivalent independent body.

Empirical work that uses a common means of measuring positive and negative states and traits related to psychological resilience.

Empirical work that evaluates the proposed psychological resilience strategies, including training interventions and programmes, during COVID-19.

Empirical and review work that targets a range of population subsets beyond frontline HCWs in a broader range of geographical locations and cultural contexts.

Empirical work that involves experimental control, longitudinal designs, naturalistic settings, and other rigorous approaches.

We conducted a systematic meta-review of literature reviews on psychological resilience during the COVID-19 pandemic. We followed the Preferred Reporting Items for Systematic review and Meta-Analysis (PRISMA) guidelines 40 with modifications for meta-reviews based on Aromataris et al. 13 . Our PRISMA checklist for the abstract is in Supplementary Table 1 and our PRISMA checklist for the article is in Supplementary Table 2 . We used the protocol available in Seaborn et al. 6 . This protocol was registered in advance of data collection with PROSPERO on February 17, 2021 under registration ID CRD42021235288.

Eligibility criteria

All types of reviews that summarised empirical work on psychological resilience in relation to the COVID-19 pandemic were included. We aimed to source only the highest quality of work available. As such, included reviews needed to be published in an academic or medical trade venue and peer reviewed as a basic criterion for quality. Publications from the start of the pandemic (January 2020) until the start of the review (June 2021) were included. Only reviews written in English were included, as this was the language known by all of the authors and the current international standard. Theory and opinion papers were not included, as they would not provide the type of summarised evidence sought for public health decision making. Inaccessible and unpublished literature reviews, including papers posted to archival websites and grey literature, were excluded because a minimum of quality could not be guaranteed.

Information sources, search strategy, and study selection

Three databases, PubMed, Scopus, and Web of Science, were searched between January 16 and 19, 2021, with an update on June 9, 2021. Full search terms and queries can be found in Supplementary Table 3 . A1, A3, and A2 conducted the searches, saving the results to Zotero and removing duplicates there. The combined list was then uploaded to Covidence. A1, A4, and A2 independently screened the papers in two phases: first based on the titles, keywords, and abstracts, and then based on the full text. A list of reviews excluded at the full text stage is available in Supplementary Table 4 . A1 and A4 divided the work and A2 screened all papers. Conflicts were resolved by involving the other reviewer.

Data collection and extraction

A1, A3, and A2 independently extracted data into a Google Sheet. A1 and A3 extracted data for about 50% of the total papers each, and A2 extracted data from all papers. A4 was assigned to resolve conflicts between the sets of data extractions. Data extraction variables were decided based on an extension of PICOS 41 for meta-reviews 13 . These included: article title, authors, year of publication, objectives, type of review, participant demographics (population subset, setting), number of databases searched, date ranges of database searches, publication date ranges of reviewed articles, number of studies, types of studies, country of origin of studies, study risk of bias/quality assessment tool used, protocol registration, citation count via Google Scholar, outcomes reported, method/s of analysis, measures of psychological resilience, their instruments, whether they were tested in COVID-19, how they were assessed (i.e., statistically), CIs, measures used to evaluate strategies, their instruments, whether they were tested in COVID-19, how they were assessed (i.e., statistically), CIs, thematic frameworks, and major finding.

Risk of bias and confidence assessments

Risk of bias and quality assessments were independently conducted by A1, A4, and A2 using a Google Form and Sheet. A1 and A4 were each responsible for about 50% of the papers, and A2 assessed all papers. We used the Scale for the Assessment of Narrative Review Articles (SANRA) 42 for qualitative reviews and the JBI Critical Appraisal Checklist for Systematic Reviews and Research Synthesis 13 for the rest. In contrast to the protocol, we did not use the AMSTAR-2 because there were too few reviews that met the characteristics required for that tool. Sums were averaged across the reviewers. Cut-offs were determined after evaluating and comparing the reviews in a weighted fashion; for both, the cut-off was set at 0.8. Only the data of reviews that met the standard of quality were used to answer RQ2. Confidence in the quality of evidence was assessed by A1 and A2 using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system 43 .

Data analysis

The planned meta-synthesis could not be conducted due to the nature of the reviews captured. As such, measures of effect, variability (i.e., heterogeneity), and other inferential statistics could not be generated. Instead, a combination of descriptive statistics and thematic analyses were generated to identify meaningful patterns across the data 44 , 45 . A3 was responsible for the descriptives. A1, A4, and A2 conducted the thematic analyses. High-level themes were inductively derived as a means of “seeing across” the corpus of review work, while most sub-themes were semantically derived, using the words found within the reviews. All thematic analyses involved a standard, rigorous process of familiarisation with the data, initial coding by one reviewer, generation of initial themes by that reviewer, independent application of those themes by two reviewers, discussion and re-review until conflicts were resolved or themes discarded, and finalisation of themes by the first reviewer. A4 was the first reviewer for the measures data. A1 was the first reviewer for the strategies and risk/protective factors data. A2 was the second reviewer in all cases. We used Google Sheets for all analyses.

Data availability

Most of the data is included in this paper and/or the Supplementary Information. All other data can be made available by the authors upon request.

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Seaborn, K., Henderson, K., Gwizdka, J. et al. A meta-review of psychological resilience during COVID-19. npj Mental Health Res 1 , 5 (2022). https://doi.org/10.1038/s44184-022-00005-8

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A literature review, also called a review article or review of literature, surveys the existing research on a topic. The term "literature" in this context refers to published research or scholarship in a particular discipline, rather than "fiction" (like American Literature) or an individual work of literature. In general, literature reviews are most common in the sciences and social sciences.

Literature reviews may be written as standalone works, or as part of a scholarly article or research paper. In either case, the purpose of the review is to summarize and synthesize the key scholarly work that has already been done on the topic at hand. The literature review may also include some analysis and interpretation. A literature review is  not  a summary of every piece of scholarly research on a topic.

Why are literature reviews useful?

Literature reviews can be very helpful for newer researchers or those unfamiliar with a field by synthesizing the existing research on a given topic, providing the reader with connections and relationships among previous scholarship. Reviews can also be useful to veteran researchers by identifying potentials gaps in the research or steering future research questions toward unexplored areas. If a literature review is part of a scholarly article, it should include an explanation of how the current article adds to the conversation. (From: https://researchguides.drake.edu/englit/criticism)

How is a literature review different from a research article?

Research articles: "are empirical articles that describe one or several related studies on a specific, quantitative, testable research question....they are typically organized into four text sections: Introduction, Methods, Results, Discussion." Source: https://psych.uw.edu/storage/writing_center/litrev.pdf)

Steps for Writing a Literature Review

1. Identify and define the topic that you will be reviewing.

The topic, which is commonly a research question (or problem) of some kind, needs to be identified and defined as clearly as possible.  You need to have an idea of what you will be reviewing in order to effectively search for references and to write a coherent summary of the research on it.  At this stage it can be helpful to write down a description of the research question, area, or topic that you will be reviewing, as well as to identify any keywords that you will be using to search for relevant research.

2. Conduct a Literature Search

Use a range of keywords to search databases such as PsycINFO and any others that may contain relevant articles.  You should focus on peer-reviewed, scholarly articles . In SuperSearch and most databases, you may find it helpful to select the Advanced Search mode and include "literature review" or "review of the literature" in addition to your other search terms.  Published books may also be helpful, but keep in mind that peer-reviewed articles are widely considered to be the “gold standard” of scientific research.  Read through titles and abstracts, select and obtain articles (that is, download, copy, or print them out), and save your searches as needed. Most of the databases you will need are linked to from the Cowles Library Psychology Research guide .

3. Read through the research that you have found and take notes.

Absorb as much information as you can.  Read through the articles and books that you have found, and as you do, take notes.  The notes should include anything that will be helpful in advancing your own thinking about the topic and in helping you write the literature review (such as key points, ideas, or even page numbers that index key information).  Some references may turn out to be more helpful than others; you may notice patterns or striking contrasts between different sources; and some sources may refer to yet other sources of potential interest.  This is often the most time-consuming part of the review process.  However, it is also where you get to learn about the topic in great detail. You may want to use a Citation Manager to help you keep track of the citations you have found. 

4. Organize your notes and thoughts; create an outline.

At this stage, you are close to writing the review itself.  However, it is often helpful to first reflect on all the reading that you have done.  What patterns stand out?  Do the different sources converge on a consensus?  Or not?  What unresolved questions still remain?  You should look over your notes (it may also be helpful to reorganize them), and as you do, to think about how you will present this research in your literature review.  Are you going to summarize or critically evaluate?  Are you going to use a chronological or other type of organizational structure?  It can also be helpful to create an outline of how your literature review will be structured.

5. Write the literature review itself and edit and revise as needed.

The final stage involves writing.  When writing, keep in mind that literature reviews are generally characterized by a  summary style  in which prior research is described sufficiently to explain critical findings but does not include a high level of detail (if readers want to learn about all the specific details of a study, then they can look up the references that you cite and read the original articles themselves).  However, the degree of emphasis that is given to individual studies may vary (more or less detail may be warranted depending on how critical or unique a given study was).   After you have written a first draft, you should read it carefully and then edit and revise as needed.  You may need to repeat this process more than once.  It may be helpful to have another person read through your draft(s) and provide feedback.

6. Incorporate the literature review into your research paper draft. (note: this step is only if you are using the literature review to write a research paper. Many times the literature review is an end unto itself).

After the literature review is complete, you should incorporate it into your research paper (if you are writing the review as one component of a larger paper).  Depending on the stage at which your paper is at, this may involve merging your literature review into a partially complete Introduction section, writing the rest of the paper around the literature review, or other processes.

These steps were taken from: https://psychology.ucsd.edu/undergraduate-program/undergraduate-resources/academic-writing-resources/writing-research-papers/writing-lit-review.html#6.-Incorporate-the-literature-r

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Association between problematic social networking use and anxiety symptoms: a systematic review and meta-analysis

• Mingxuan Du 1 ,
• Chengjia Zhao 2 ,
• Haiyan Hu 1 ,
• Ningning Ding 1 ,
• Jiankang He 1 ,
• Wenwen Tian 1 ,
• Wenqian Zhao 1 ,
• Xiujian Lin 1 ,
• Gaoyang Liu 1 ,
• Wendan Chen 1 ,
• ShuangLiu Wang 1 ,
• Pengcheng Wang 3 ,
• Dongwu Xu 1 ,
• Xinhua Shen 4 &
• Guohua Zhang 1  

BMC Psychology volume  12 , Article number:  263 ( 2024 ) Cite this article

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A growing number of studies have reported that problematic social networking use (PSNU) is strongly associated with anxiety symptoms. However, due to the presence of multiple anxiety subtypes, existing research findings on the extent of this association vary widely, leading to a lack of consensus. The current meta-analysis aimed to summarize studies exploring the relationship between PSNU levels and anxiety symptoms, including generalized anxiety, social anxiety, attachment anxiety, and fear of missing out. 209 studies with a total of 172 articles were included in the meta-analysis, involving 252,337 participants from 28 countries. The results showed a moderately positive association between PSNU and generalized anxiety (GA), social anxiety (SA), attachment anxiety (AA), and fear of missing out (FoMO) respectively (GA: r  = 0.388, 95% CI [0.362, 0.413]; SA: r  = 0.437, 95% CI [0.395, 0.478]; AA: r  = 0.345, 95% CI [0.286, 0.402]; FoMO: r  = 0.496, 95% CI [0.461, 0.529]), and there were different regulatory factors between PSNU and different anxiety subtypes. This study provides the first comprehensive estimate of the association of PSNU with multiple anxiety subtypes, which vary by time of measurement, region, gender, and measurement tool.

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Introduction

Social network refers to online platforms that allow users to create, share, and exchange information, encompassing text, images, audio, and video [ 1 ]. The use of social network, a term encompassing various activities on these platforms, has been measured from angles such as frequency, duration, intensity, and addictive behavior, all indicative of the extent of social networking usage [ 2 ]. As of April 2023, there are 4.8 billion social network users globally, representing 59.9% of the world’s population [ 3 ]. The usage of social network is considered a normal behavior and a part of everyday life [ 4 , 5 ]. Although social network offers convenience in daily life, excessive use can lead to PSNU [ 6 , 7 ], posing potential threats to mental health, particularly anxiety symptoms (Rasmussen et al., 2020). Empirical research has shown that anxiety symptoms, including generalized anxiety (GA), social anxiety (SA), attachment anxiety (AA), and fear of missing out (FoMO), are closely related to PSNU [ 8 , 9 , 10 , 11 , 12 ]. While some empirical studies have explored the relationship between PSNU and anxiety symptoms, their conclusions are not consistent. Some studies have found a significant positive correlation [ 13 , 14 , 15 ], while others have found no significant correlation [ 16 , 17 , 18 , 19 ]. Furthermore, the degree of correlation varies widely in existing research, with reported r-values ranging from 0.12 to 0.80 [ 20 , 21 ]. Therefore, a systematic meta-analysis is necessary to clarify the impact of PSNU on individual anxiety symptoms.

Previous research lacks a unified concept of PSNU, primarily due to differing theoretical interpretations by various authors, and the use of varied standards and diagnostic tools. Currently, this phenomenon is referred to by several terms, including compulsive social networking use, problematic social networking use, excessive social networking use, social networking dependency, and social networking addiction [ 22 , 23 , 24 , 25 , 26 ]. These conceptual differences hinder the development of a cohesive and systematic research framework, as it remains unclear whether these definitions and tools capture the same underlying construct [ 27 ]. To address this lack of uniformity, this paper will use the term “problematic use” to encompass all the aforementioned nomenclatures (i.e., compulsive, excessive, dependent, and addictive use).

Regarding the relationship between PSNU and anxiety symptoms, two main perspectives exist: the first suggests a positive correlation, while the second proposes a U-shaped relationship. The former perspective, advocating a positive correlation, aligns with the social cognitive theory of mass communication. It posits that PSNU can reinforce certain cognitions, emotions, attitudes, and behaviors [ 28 , 29 ], potentially elevating individuals’ anxiety levels [ 30 ]. Additionally, the cognitive-behavioral model of pathological use, a primary framework for explaining factors related to internet-based addictions, indicates that psychiatric symptoms like depression or anxiety may precede internet addiction, implying that individuals experiencing anxiety may turn to social networking platforms as a coping mechanism [ 31 ]. Empirical research also suggests that highly anxious individuals prefer computer-mediated communication due to the control and social liberation it offers and are more likely to have maladaptive emotional regulation, potentially leading to problematic social network service use [ 32 ]. Turning to the alternate perspective, it proposes a U-shaped relationship as per the digital Goldilocks hypothesis. In this view, moderate social networking usage is considered beneficial for psychosocial adaptation, providing individuals with opportunities for social connection and support. Conversely, both excessive use and abstinence can negatively impact psychosocial adaptation [ 33 ]. In summary, both perspectives offer plausible explanations.

Incorporating findings from previous meta-analyses, we identified seven systematic reviews and two meta-analyses that investigated the association between PSNU and anxiety. The results of these meta-analyses indicated a significant positive correlation between PSNU and anxiety (ranging from 0.33 to 0.38). However, it is evident that these previous meta-analyses had certain limitations. Firstly, they focused only on specific subtypes of anxiety; secondly, they were limited to adolescents and emerging adults in terms of age. In summary, this systematic review aims to ascertain which theoretical perspective more effectively explains the relationship between PSNU and anxiety, addressing the gaps in previous meta-analyses. Additionally, the association between PSNU and anxiety could be moderated by various factors. Drawing from a broad research perspective, any individual study is influenced by researcher-specific designs and associated sample estimates. These may lead to bias compared to the broader population. Considering the selection criteria for moderating variables in empirical studies and meta-analyses [ 34 , 35 ], the heterogeneity of findings on problematic social network usage and anxiety symptoms could be driven by divergence in sample characteristics (e.g., gender, age, region) and research characteristics (measurement instrument of study variables). Since the 2019 coronavirus pandemic, heightened public anxiety may be attributed to the fear of the virus or heightened real life stress. The increased use of electronic devices, particularly smartphones during the pandemic, also instigates the prevalence of problematic social networking. Thus, our analysis focuses on three moderators: sample characteristics (participants’ gender, age, region), measurement tools (for PSNU and anxiety symptoms) and the time of measurement (before COVID-19 vs. during COVID-19).

The present study was conducted in accordance with the 2020 statement on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [ 36 ]. To facilitate transparency and to avoid unnecessary duplication of research, this study was registered on PROSPERO, and the number is CRD42022350902.

Literature search

Studies on the relationship between the PSNU and anxiety symptoms from 2000 to 2023 were retrieved from seven databases. These databases included China National Knowledge Infrastructure (CNKI), Wanfang Data, Chongqing VIP Information Co. Ltd. (VIP), Web of Science, ScienceDirect, PubMed, and PsycARTICLES. The search strings consisted of (a) anxiety symptoms, (b) social network, and (c) Problematic use. As shown in Table  1 , the keywords for anxiety are as follows: anxiety, generalized anxiety, social anxiety, attachment anxiety, fear of missing out, and FoMO. The keywords for social network are as follows: social network, social media, social networking site, Instagram, and Facebook. The keywords for addiction are as follows: addiction, dependence, problem/problematic use, excessive use. The search deadline was March 19, 2023. A total of 2078 studies were initially retrieved and all were identified ultimately.

Inclusion and exclusion criteria

Retrieved studies were eligible for the present meta-analysis if they met the following inclusion criteria: (a) the study provided Pearson correlation coefficients used to measure the relationship between PSNU and anxiety symptoms; (b) the study reported the sample size and the measurement instruments for the variables; (c) the study was written in English and Chinese; (d) the study provided sufficient statistics to calculate the effect sizes; (e) effect sizes were extracted from independent samples. If multiple independent samples were investigated in the same study, they were coded separately; if the study was a longitudinal study, they were coded by the first measurement. In addition, studies were excluded if they: (a) examined non-problematic social network use; (b) had an abnormal sample population; (c) the results of the same sample were included in another study and (d) were case reports or review articles. Two evaluators with master’s degrees independently assessed the eligibility of the articles. A third evaluator with a PhD examined the results and resolved dissenting views.

Data extraction and quality assessment

Two evaluators independently coded the selected articles according to the following characteristics: literature information, time of measurement (before the COVID-19 vs. during the COVID-19), sample source (developed country vs. developing country), sample size, proportion of males, mean age, type of anxiety, and measurement instruments for PSNU and anxiety symptoms. The following principles needed to be adhered to in the coding process: (a) effect sizes were extracted from independent samples. If multiple independent samples were investigated in the same study, they were coded separately; if the study was a longitudinal study, it was coded by the first measurement; (b) if multiple studies used the same data, the one with the most complete information was selected; (c) If studies reported t or F values rather than r , the following formula \( r=\sqrt{\frac{{t}^{2}}{{t}^{2}+df}}\) ; \( r=\sqrt{\frac{F}{F+d{f}_{e}}}\) was used to convert them into r values [ 37 , 38 ]. Additionally, if some studies only reported the correlation matrix between each dimension of PSNU and anxiety symptoms, the following formula \( {r}_{xy}=\frac{\sum {r}_{xi}{r}_{yj}}{\sqrt{n+n(n-1){r}_{xixj}}\sqrt{m+m(m-1){r}_{yiyj}}}\) was used to synthesize the r values [ 39 ], where n or m is the number of dimensions of variable x or variable y, respectively, and \( {r}_{xixj} \) or \( {r}_{yiyj}\) represents the mean of the correlation coefficients between the dimensions of variable x or variable y, respectively.

Literature quality was determined according to the meta-analysis quality evaluation scale developed [ 40 ]. The quality of the post-screening studies was assessed by five dimensions: sampling method, efficiency of sample collection, level of publication, and reliability of PSNU and anxiety symptom measurement instruments. The total score of the scale ranged from 0 to 10; higher scores indicated better quality of the literature.

Data analysis

All data were performed using Comprehensive Meta Analysis 3.3 (CMA 3.3). Pearson’s product-moment coefficient r was selected as the effect size index in this meta-analysis. Firstly, \( {\text{F}\text{i}\text{s}\text{h}\text{e}\text{r}}^{{\prime }}\text{s} Z=\frac{1}{2}\times \text{ln}\left(\frac{1+r}{1-r}\right)\) was used to convert the correlation coefficient to Fisher Z . Then the formula \( SE=\sqrt{\frac{1}{n-3}}\) was used to calculate the standard error ( SE ). Finally, the summary of r was obtained from the formula \( r=\frac{{e}^{2z}-1}{{e}^{2z}+1}\) for a comprehensive measure of the relationship between PSNU and anxiety symptoms [ 37 , 41 ].

Although the effect sizes estimated by the included studies may be similar, considering the actual differences between studies (e.g., region and gender), the random effects model was a better choice for data analysis for the current meta-analysis. The heterogeneity of the included study effect sizes was measured for significance by Cochran’s Q test and estimated quantitatively by the I 2 statistic [ 42 ]. If the results indicate there is a significant heterogeneity (the Q test: p -value < 0.05, I 2  > 75) and the results of different studies are significantly different from the overall effect size. Conversely, it indicates there are no differences between the studies and the overall effect size. And significant heterogeneity tends to indicate the possible presence of potential moderating variables. Subgroup analysis and meta-regression analysis were used to examine the moderating effect of categorical and continuous variables, respectively.

Funnel plots, fail-safe number (Nfs) and Egger linear regression were utilized to evaluate the publication bias [ 43 , 44 , 45 ]. The likelihood of publication bias was considered low if the intercept obtained from Egger linear regression was not significant. A larger Nfs indicated a lower risk of publication bias, and if Nfs < 5k + 10 (k representing the original number of studies), publication bias should be a concern [ 46 ]. When Egger’s linear regression was significant, the Duval and Tweedie’s trim-and-fill was performed to correct the effect size. If there was no significant change in the effect size, it was assumed that there was no serious publication bias [ 47 ].

A significance level of P  < 0.05 was deemed applicable in this study.

Sample characteristics

The PRISMA search process is depicted in Fig.  1 . The database search yielded 2078 records. After removing duplicate records and screening the title and abstract, the full text was subject to further evaluation. Ultimately, 172 records fit the inclusion criteria, including 209 independent effect sizes. The present meta-analysis included 68 studies on generalized anxiety, 44 on social anxiety, 22 on attachment anxiety, and 75 on fear of missing out. The characteristics of the selected studies are summarized in Table  2 . The majority of the sample group were adults. Quality scores for selected studies ranged from 0 to 10, with only 34 effect sizes below the theoretical mean, indicating high quality for the included studies. The literature included utilized BSMAS as the primary tool to measure PSNU, DASS-21-A to measure GA, IAS to measure SA, ECR to measure AA, and FoMOS to measure FoMO.

Flow chart of the search and selection strategy

Overall analysis, homogeneity tests and publication bias

As shown in Table  3 , there was significant heterogeneity between PSNU and all four anxiety symptoms (GA: Q  = 1623.090, I 2  = 95.872%; SA: Q  = 1396.828, I 2  = 96.922%; AA: Q  = 264.899, I 2  = 92.072%; FoMO: Q  = 1847.110, I 2  = 95.994%), so a random effects model was chosen. The results of the random effects model indicate a moderate positive correlation between PSNU and anxiety symptoms (GA: r  = 0.350, 95% CI [0.323, 0.378]; SA: r  = 0.390, 95% CI [0.347, 0.431]; AA: r  = 0.345, 95% CI [0.286, 0.402]; FoMO: r  = 0.496, 95% CI [0.461, 0.529]).

Figure  2 shows the funnel plot of the relationship between PSNU and anxiety symptoms. No significant symmetry was seen in the funnel plot of the relationship between PSNU and GA and between PSNU and SA. And the Egger’s regression results also indicated that there might be publication bias ( t  = 3.775, p  < 0.001; t  = 2.309, p  < 0.05). Therefore, it was necessary to use fail-safe number (Nfs) and the trim and fill method for further examination and correction. The Nfs for PSNU and GA as well as PSNU and SA are 4591 and 7568, respectively. Both Nfs were much larger than the standard 5 k  + 10. After performing the trim and fill method, 14 effect sizes were added to the right side of the funnel plat (Fig.  2 .a), the correlation coefficient between PSNU and GA changed to ( r  = 0.388, 95% CI [0.362, 0.413]); 10 effect sizes were added to the right side of the funnel plat (Fig.  2 .b), the correlation coefficient between PSNU and SA changed to ( r  = 0.437, 95% CI [0.395, 0.478]). The correlation coefficients did not change significantly, indicating that there was no significant publication bias associated with the relationship between PSNU and these two anxiety symptoms (GA and SA).

Funnel plot of the relationship between PSNU and anxiety symptoms. Note: Black dots indicated additional studies after using trim and fill method; ( a ) = Funnel plot of the PSNU and GA; ( b ) = Funnel plot of the PSNU and SA; ( c ) = Funnel plot of the PSNU and AA; ( d ) = Funnel plot of the PSNU and FoMO

Sensitivity analyses

Initially, the findings obtained through the one-study-removed approach indicated that the heterogeneities in the relationship between PSNU and anxiety symptoms were not attributed to any individual study. Nevertheless, it is important to note that sensitivity analysis should be performed based on literature quality [ 223 ] since low-quality literature could potentially impact result stability. In the relationship between PSNU and GA, the 10 effect sizes below the theoretical mean scores were excluded from analysis, and the sensitivity analysis results were recalculated ( r  = 0.402, 95% CI [0.375, 0.428]); In the relationship between PSNU and SA, the 8 effect sizes below the theoretical mean scores were excluded from analysis, and the sensitivity analysis results were recalculated ( r  = 0.431, 95% CI [0.387, 0.472]); In the relationship between PSNU and AA, the 5 effect sizes below the theoretical mean scores were excluded from analysis, and the sensitivity analysis results were recalculated ( r  = 0.367, 95% CI [0.298, 0.433]); In the relationship between PSNU and FoMO, the 11 effect sizes below the theoretical mean scores were excluded from analysis, and the sensitivity analysis results were recalculated ( r  = 0.508, 95% CI [0.470, 0.544]). The revised estimates indicate that meta-analysis results were stable.

Moderator analysis

The impact of moderator variables on the relation between psnu and ga.

The results of subgroup analysis and meta-regression are shown in Table  4 , the time of measurement significantly moderated the correlation between PSNU and GA ( Q between = 19.268, df  = 2, p  < 0.001). The relation between the two variables was significantly higher during the COVID-19 ( r  = 0.392, 95% CI [0.357, 0.425]) than before the COVID-19 ( r  = 0.270, 95% CI [0.227, 0.313]) or measurement time uncertain ( r  = 0.352, 95% CI [0.285, 0.415]).

The moderating effect of the PSNU measurement was significant ( Q between = 6.852, df  = 1, p  = 0.009). The relation was significantly higher when PSNU was measured with the BSMAS ( r  = 0.373, 95% CI [0.341, 0.404]) compared to others ( r  = 0.301, 95% CI [0.256, 0.344]).

The moderating effect of the GA measurement was significant ( Q between = 60.061, df  = 5, p  < 0.001). Specifically, when GA measured by the GAD ( r  = 0.398, 95% CI [0.356, 0.438]) and the DASS-21-A ( r  = 0.433, 95% CI [0.389, 0.475]), a moderate positive correlation was observed. However, the correlation was less significant when measured using the STAI ( r  = 0.232, 95% CI [0.187, 0.276]).

For the relation between PSNU and GA, the moderating effect of region, gender and age were not significant.

The impact of moderator variables on the relation between PSNU and SA

The effects of the moderating variables in the relation between PSNU and SA were shown in Table  5 . The results revealed a gender-moderated variances between the two variables (b = 0.601, 95% CI [ 0.041, 1.161], Q model (1, k = 41) = 4.705, p  = 0.036).

For the relation between PSNU and SA, the moderating effects of time of measurement, region, measurement of PSNU and SA, and age were not significant.

The impact of moderator variables on the relation between PSNU and AA

The effects of the moderating variables in the relation between PSNU and AA were shown in Table  6 , region significantly moderated the correlation between PSNU and AA ( Q between = 6.410, df  = 2, p  = 0.041). The correlation between the two variables was significantly higher in developing country ( r  = 0.378, 95% CI [0.304, 0.448]) than in developed country ( r  = 0.242, 95% CI [0.162, 0.319]).

The moderating effect of the PSNU measurement was significant ( Q between = 6.852, df  = 1, p  = 0.009). Specifically, when AA was measured by the GPIUS-2 ( r  = 0.484, 95% CI [0.200, 0.692]) and the PMSMUAQ ( r  = 0.443, 95% CI [0.381, 0.501]), a moderate positive correlation was observed. However, the correlation was less significant when measured using the BSMAS ( r  = 0.248, 95% CI [0.161, 0.331]) and others ( r  = 0.313, 95% CI [0.250, 0.372]).

The moderating effect of the AA measurement was significant ( Q between = 17.283, df  = 2, p  < 0.001). The correlation was significantly higher when measured using the ECR ( r  = 0.386, 95% CI [0.338, 0.432]) compared to the RQ ( r  = 0.200, 95% CI [0.123, 0.275]).

For the relation between PSNU and AA, the moderating effects of time of measurement, region, gender, and age were not significant.

The impact of moderator variables on the relation between PSNU and FoMO

The effects of the moderating variables in the relation between PSNU and FoMO were shown in Table  7 , the moderating effect of the PSNU measurement was significant ( Q between = 8.170, df  = 2, p  = 0.017). Among the sub-dimensions, the others was excluded because there was only one sample. Specifically, when measured using the FoMOS-MSME ( r  = 0.630, 95% CI [0.513, 0.725]), a moderate positive correlation was observed. However, the correlation was less significant when measured using the FoMOS ( r  = 0.472, 95% CI [0.432, 0.509]) and the T-S FoMOS ( r  = 0.557, 95% CI [0.463, 0.639]).

For the relationship between PSNU and FoMO, the moderating effects of time of measurement, region, measurement of PSNU, gender and age were not significant.

Through systematic review and meta-analysis, this study established a positive correlation between PSNU and anxiety symptoms (i.e., generalized anxiety, social anxiety, attachment anxiety, and fear of missing out), confirming a linear relationship and partially supporting the Social Cognitive Theory of Mass Communication [ 28 ] and the Cognitive Behavioral Model of Pathological Use [ 31 ]. Specifically, a significant positive correlation between PSNU and GA was observed, implying that GA sufferers might resort to social network for validation or as an escape from reality, potentially alleviating their anxiety. Similarly, the meta-analysis demonstrated a strong positive correlation between PSNU and SA, suggesting a preference for computer-mediated communication among those with high social anxiety due to perceived control and liberation offered by social network. This preference is often accompanied by maladaptive emotional regulation, predisposing them to problematic use. In AA, a robust positive correlation was found with PSNU, indicating a higher propensity for such use among individuals with attachment anxiety. Notably, the study identified the strongest correlation in the context of FoMO. FoMO’s significant association with PSNU is multifaceted, stemming from the real-time nature of social networks that engenders a continuous concern about missing crucial updates or events. This drives frequent engagement with social network, thereby establishing a direct link to problematic usage patterns. Additionally, social network’s feedback loops amplify this effect, intensifying FoMO. The culture of social comparison on these platforms further exacerbates FoMO, as users frequently compare their lives with others’ selectively curated portrayals, enhancing both their social networking usage frequency and the pursuit for social validation. Furthermore, the integral role of social network in modern life broadens FoMO’s scope, encompassing anxieties about staying informed and connected.

The notable correlation between FoMO and PSNU can be comprehensively understood through various perspectives. FoMO is inherently linked to the real-time nature of social networks, which cultivates an ongoing concern about missing significant updates or events in one’s social circle [ 221 ]. This anxiety prompts frequent engagement with social network, leading to patterns of problematic use. Moreover, the feedback loops in social network algorithms, designed to enhance user engagement, further intensify this fear [ 224 ]. Additionally, social comparison, a common phenomenon on these platforms, exacerbates FoMO as users continuously compare their lives with the idealized representations of others, amplifying feelings of missing out on key social experiences [ 225 ]. This behavior not only increases social networking usage but also is closely linked to the quest for social validation and identity construction on these platforms. The extensive role of social network in modern life further amplifies FoMO, as these platforms are crucial for information exchange and maintaining social ties. FoMO thus encompasses more than social concerns, extending to anxieties about staying informed with trends and dynamics within social networks [ 226 ]. The multifaceted nature of FoMO in relation to social network underscores its pronounced correlation with problematic social networking usage. In essence, the combination of social network’s intrinsic characteristics, psychological drivers of user behavior, the culture of social comparison, and the pervasiveness of social network in everyday life collectively make FoMO the most pronouncedly correlated anxiety type with PSNU.

Additionally, we conducted subgroup analyses on the timing of measurement (before COVID-19 vs. during COVID-19), measurement tools (for PSNU and anxiety symptoms), sample characteristics (participants’ region), and performed a meta-regression analysis on gender and age in the context of PSNU and anxiety symptoms. It was found that the timing of measurement, tools used for assessing PSNU and anxiety, region, and gender had a moderating effect, whereas age did not show a significant moderating impact.

Firstly, the relationship between PSNU and anxiety symptoms was significantly higher during the COVID-19 period than before, especially between PSNU and GA. However, the moderating effect of measurement timing was not significant in the relationship between PSNU and other types of anxiety. This could be attributed to the increased uncertainty and stress during the pandemic, leading to heightened levels of general anxiety [ 227 ]. The overuse of social network for information seeking and anxiety alleviation might have paradoxically exacerbated anxiety symptoms, particularly among individuals with broad future-related worries [ 228 ]. While the COVID-19 pandemic altered the relationship between PSNU and GA, its impact on other types of anxiety (such as SA and AA) may not have been significant, likely due to these anxiety types being more influenced by other factors like social skills and attachment styles, which were minimally impacted by the epidemic.

Secondly, the observed variance in the relationship between PSNU and AA across different economic contexts, notably between developing and developed countries, underscores the multifaceted influence of socio-economic, cultural, and technological factors on this dynamic. The amplified connection in developing countries may be attributed to greater socio-economic challenges, distinct cultural norms regarding social support and interaction, rising social network penetration, especially among younger demographics, and technological disparities influencing accessibility and user experience [ 229 , 230 ]. Moreover, the role of social network as a coping mechanism for emotional distress, potentially fostering insecure attachment patterns, is more pronounced in these settings [ 231 ]. These findings highlight the necessity of considering contextual variations in assessing the psychological impacts of social network, advocating for a nuanced understanding of how socio-economic and cultural backgrounds mediate the relationship between PSNU and mental health outcomes [ 232 ]. Additionally, the relationship between PSNU and other types of anxiety (such as GA and SA) presents uniform characteristics across different economic contexts.

Thirdly, the significant moderating effects of measurement tools in the context of PSNU and its correlation with various forms of anxiety, including GA, and AA, are crucial in interpreting the research findings. Specifically, the study reveals that the Bergen Social Media Addiction Scale (BSMAS) demonstrates a stronger correlation between PSNU and GA, compared to other tools. Similarly, for AA, the Griffiths’ Problematic Internet Use Scale 2 (GPIUS2) and the Problematic Media Social Media Use Assessment Questionnaire (PMSMUAQ) show a more pronounced correlation with AA than the BSMAS or other instruments, but for SA and FoMO, the PSNU instrument doesn’t significantly moderate the correlation. The PSNU measurement tool typically contains an emotional change dimension. SA and FoMO, due to their specific conditional stimuli triggers and correlation with social networks [ 233 , 234 ], are likely to yield more consistent scores in this dimension, while GA and AA may be less reliable due to their lesser sensitivity to specific conditional stimuli. Consequently, the adjustment effects of PSNU measurements vary across anxiety symptoms. Regarding the measurement tools for anxiety, different scales exhibit varying degrees of sensitivity in detecting the relationship with PSNU. The Generalized Anxiety Disorder Scale (GAD) and the Depression Anxiety Stress Scales 21 (DASS-21) are more effective in illustrating a strong relationship between GA and PSNU than the State-Trait Anxiety Inventory (STAI). In the case of AA, the Experiences in Close Relationships-21 (ECR-21) provides a more substantial correlation than the Relationship Questionnaire (RQ). Furthermore, for FoMO, the Fear of Missing Out Scale - Multi-Social Media Environment (FoMOS-MSME) is more indicative of a strong relationship with PSNU compared to the standard FoMOS or the T-S FoMOS. These findings underscore the importance of the selection of appropriate measurement tools in research. Different tools, due to their unique design, focus, and sensitivity, can reveal varying degrees of correlation between PSNU and anxiety disorders. This highlights the need for careful consideration of tool characteristics and their potential impact on research outcomes. It also cautions against drawing direct comparisons between studies without acknowledging the possible variances introduced by the use of different measurement instruments.

Fourthly, the significant moderating role of gender in the relationship between PSNU and SA, particularly pronounced in samples with a higher proportion of females. Women tend to engage more actively and emotionally with social network, potentially leading to an increased dependency on these platforms when confronting social anxiety [ 235 ]. This intensified use might amplify the association between PSNU and SA. Societal and cultural pressures, especially those related to appearance and social status, are known to disproportionately affect women, possibly exacerbating their experience of social anxiety and prompting a greater reliance on social network for validation and support [ 236 ]. Furthermore, women’s propensity to seek emotional support and express themselves on social network platforms [ 237 ] could strengthen this link, particularly in the context of managing social anxiety. Consequently, the observed gender differences in the relationship between PSNU and SA underscore the importance of considering gender-specific dynamics and cultural influences in psychological research related to social network use. In addition, gender consistency was observed in the association between PSNU and other types of anxiety, indicating no significant gender disparities.

Fifthly, the absence of a significant moderating effect of age on the relationship between PSNU and various forms of anxiety suggests a pervasive influence of social network across different age groups. This finding indicates that the impact of PSNU on anxiety is relatively consistent, irrespective of age, highlighting the universal nature of social network’s psychological implications [ 238 ]. Furthermore, this uniformity suggests that other factors, such as individual psychological traits or socio-cultural influences, might play a more crucial role in the development of anxiety related to social networking usage than age [ 239 ]. The non-significant role of age also points towards a potential generational overlap in social networking usage patterns and their psychological effects, challenging the notion that younger individuals are uniquely susceptible to the adverse effects of social network on mental health [ 240 ]. Therefore, this insight necessitates a broader perspective in understanding the dynamics of social network and mental health, one that transcends age-based assumptions.

Limitations

There are some limitations in this research. First, most of the studies were cross-sectional surveys, resulting in difficulties in inferring causality of variables, longitudinal study data will be needed to evaluate causal interactions in the future. Second, considerable heterogeneity was found in the estimated results, although heterogeneity can be partially explained by differences in study design (e.g., Time of measurement, region, gender, and measurement tools), but this can introduce some uncertainty in the aggregation and generalization of the estimated results. Third, most studies were based on Asian samples, which limits the generality of the results. Fourth, to minimize potential sources of heterogeneity, some less frequently used measurement tools were not included in the classification of measurement tools, which may have some impact on the results of heterogeneity interpretation. Finally, since most of the included studies used self-reported scales, it is possible to get results that deviate from the actual situation to some extent.

This meta-analysis aims to quantifies the correlations between PSNU and four specific types of anxiety symptoms (i.e., generalized anxiety, social anxiety, attachment anxiety, and fear of missing out). The results revealed a significant moderate positive association between PSNU and each of these anxiety symptoms. Furthermore, Subgroup analysis and meta-regression analysis indicated that gender, region, time of measurement, and instrument of measurement significantly influenced the relationship between PSNU and specific anxiety symptoms. Specifically, the measurement time and GA measurement tools significantly influenced the relationship between PSNU and GA. Gender significantly influenced the relationship between PSNU and SA. Region, PSNU measurement tools, and AA measurement tools all significantly influenced the relationship between PSNU and AA. The FoMO measurement tool significantly influenced the relationship between PSNU and FoMO. Regarding these findings, prevention interventions for PSNU and anxiety symptoms are important.

Data availability

The datasets are available from the corresponding author on reasonable request.

Abbreviations

• Problematic social networking use
• Generalized anxiety
• Social anxiety
• Attachment anxiety

Fear of miss out

Bergen Social Media Addiction Scale

Facebook Addiction Scale

Facebook Intrusion Questionnaire

Generalized Problematic Internet Use Scale 2

Problematic Mobile Social Media Usage Assessment Questionnaire

Social Network Addiction Tendency Scale

Brief Symptom Inventory

The anxiety subscale of the Depression Anxiety Stress Scales

Generalized Anxiety Disorder

The anxiety subscale of the Hospital Anxiety and Depression Scale

State-Trait Anxiety Inventory

Interaction Anxiousness Scale

Liebowitz Social Anxiety Scale

Social Anxiety Scale for Social Media Users

Social Anxiety for Adolescents

Social Anxiety Subscale of the Self-Consciousness Scale

Social Interaction Anxiety Scale

Experiences in Close Relationship Scale

Relationship questionnaire

Fear of Missing Out Scale

FoMO Measurement Scale in the Mobile Social Media Environment

Trait-State Fear of missing Out Scale

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This research was supported by the Social Science Foundation of China (Grant Number: 23BSH135).

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Mingxuan Du, Haiyan Hu, Ningning Ding, Jiankang He, Wenwen Tian, Wenqian Zhao, Xiujian Lin, Gaoyang Liu, Wendan Chen, ShuangLiu Wang, Dongwu Xu & Guohua Zhang

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Du, M., Zhao, C., Hu, H. et al. Association between problematic social networking use and anxiety symptoms: a systematic review and meta-analysis. BMC Psychol 12 , 263 (2024). https://doi.org/10.1186/s40359-024-01705-w

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SYSTEMATIC REVIEW article

Research of visual attention networks in deaf individuals: a systematic review.

• 1 Department of Psychology, University of Almería, Almería, Spain
• 2 CIBIS Research Center, University of Almería, Almería, Spain
• 3 Growing Brains, Washington, DC, United States

The impact of deafness on visual attention has been widely discussed in previous research. It has been noted that deficiencies and strengths of previous research can be attributed to temporal or spatial aspects of attention, as well as variations in development and clinical characteristics. Visual attention is categorized into three networks: orienting (exogenous and endogenous), alerting (phasic and tonic), and executive control. This study aims to contribute new neuroscientific evidence supporting this hypothesis. This paper presents a systematic review of the international literature from the past 15 years focused on visual attention in the deaf population. The final review included 24 articles. The function of the orienting network is found to be enhanced in deaf adults and children, primarily observed in native signers without cochlear implants, while endogenous orienting is observed only in the context of gaze cues in children, with no differences found in adults. Results regarding alerting and executive function vary depending on clinical characteristics and paradigms used. Implications for future research on visual attention in the deaf population are discussed.

1 Introduction

1.1 background.

Early auditory deprivation is recognized as a factor influencing the development of visual attention in deaf individuals ( Colmenero et al., 2004 ; Bavelier et al., 2006 ; Stevens and Neville, 2006 ). However, existing evidence on the nature of this effect is conflicting and, crucially for the present review, unclear concerning the temporal versus spatial distribution of visual attention. Historically, research on this topic has been centered on two seemingly opposing hypotheses: the deficiency hypothesis, positing that early profound deafness leads to visual attention deficits, and the enhancement hypothesis, suggesting compensatory changes to visual attention processes ( Dye and Bavelier, 2010 ).

According to the deficiency hypothesis , integrating information from different senses is essential for the normal development of attention functioning within each sensory modality. Consequently, the absence of auditory input results in underdeveloped selective attention capacities. For deaf individuals, the lack of audition impairs the development of multisensory integration, thereby impeding the typical development of visual attention skills. Put simply, while hearing people can selectively attend to a narrow visual field and still monitor the broader environment through sounds, deaf individuals must use vision to accomplish both specific tasks and monitor the broader environment ( Smith et al., 1998 ).

This view has been primarily supported by studies examining sustained visual attention or vigilance using the Continuous Performance Test or “CPT.” For example, using the Gordon Diagnostic System (GDS), a widely used CPT, the participant is presented with digits and must respond when a “1” is followed by a “9” for around 10 min ( Dye and Hauser, 2014 ). These studies have found consistent underperformance in CPTs among the deaf population, indicating that auditory input plays a role in organizing visual attention. These results are consistent with a deficit view of cross-modal reorganization stemming from early sensory deprivation ( Mitchell and Quittner, 1996 ; Smith et al., 1998 ; Quittner et al., 2004 ).

Although CPTs have been widely used to assess sustained visual attention, these tasks are sensitive to certain additional cognitive factors ( Parasnis et al., 2003 ). Specifically, CPTs require sustained attention and the ability to hold information about the target sequence in working memory, and performance is negatively affected by the inability to inhibit responses to non-target stimuli.

In contrast to the deficiency hypothesis, the enhancement hypothesis or compensation view is based on the common assumption that deficits in one sensory modality lead to heightened sensitivities in the remaining modalities ( Bavelier et al., 2006 ). In the case of early deafness, this perspective posits that the visual system is reorganized to compensate for the lack of auditory input. Consequently, visual skills assume the functional roles previously performed by audition in the typically developing child, such as monitoring the environment or discriminating temporally complex stimuli ( Bottari et al., 2014 ; Benetti et al., 2017 ; Bola et al., 2017 ; Seymour et al., 2017 ).

The enhancement or compensation hypothesis has primarily received support from studies measuring the allocation of attention across space. The results of these studies suggest that in deaf individuals, there is a spatial redistribution of visual attention toward the periphery, allowing them to better monitor their peripheral environment based on visual rather than auditory cues ( Loke and Song, 1991 ; Sladen et al., 2005 ). For example, deaf individuals can be faster than hearing controls in detecting the onset of peripheral visual targets ( Chen et al., 2006 ; Bottari et al., 2010 ; Codina et al., 2011 , 2017 ) or in discriminating the direction of visual motion with attention to peripheral locations ( Neville and Lawson, 1987 ; Bavelier et al., 2001 ).

This redistribution of visual attention can alter the trade-off in the responses of deaf people to the periphery versus the centre. Specifically, in situations where central and peripheral static stimuli compete for selective attention resources, deaf participants are more likely to orient visual attention toward peripheral than central locations ( Sladen et al., 2005 ; Chen et al., 2006 ). Consistent with these findings, Proksch and Bavelier (2002) observed that deaf individuals are more distracted by irrelevant peripheral information, whereas hearing individuals are more distracted by irrelevant central information. However, while deaf individuals have been shown to possess a field of view that extends further toward the periphery than hearing controls ( Sladen et al., 2005 ), no differences between deaf individuals and hearing controls have been documented when processing targets presented toward the centre of the visual field ( Neville and Lawson, 1987 ; Loke and Song, 1991 ).

In an initial review conducted by Tharpe et al. (2008) to examine evidence-based literature on visual attention and deafness, various paradigms were explored, including the CPT, the letter cancellation task, and conflict tasks. No conclusive evidence was found to support general enhancement or deficits in visual attention or enhanced fundamental visual sensory abilities ( Tharpe et al., 2002 ). Rather, the authors propose that the variability in performance across these paradigms could be explained by the extensive allocation of attentional resources across the visual field, driven by increased monitoring demands. This hypothesis explains why deaf individuals tend to show poorer performance on tasks requiring sustained attention to central stimuli over time compared to those involving the detection of peripheral stimuli. This idea has been supported by results found using a modified flanker paradigm incorporating several degrees of distance between distractor and target ( Sladen et al., 2005 ).

Functional brain studies have also revealed significant differences between deaf and hearing individuals that support the compensation view. These differences are related to alterations in the visual areas and the activation of visual and attention-related brain networks. For instance, Bavelier et al. (2001) found that the absence of auditory input and sign language use in the deaf population was associated with greater activation of visual cortex areas when processing peripheral and moving stimuli. Furthermore, Mayberry et al. (2011) reported that deaf individuals exhibited greater activation of visual and attention-related brain networks during peripheral visual tasks.

An area of the cortex that has been extensively studied in the context of deafness is the middle temporal (MT) or medial superior temporal (MST) area. MT/MST areas play a key role in detecting and analyzing movement and activity in these areas is modulated by attentional processes ( O’Craven et al., 1997 ). When observing unattended moving stimuli, both deaf and hearing participants show similar recruitment of the MT/MST cortex. However, when required to attend to peripheral movement and ignore concurrent central motion, enhanced recruitment of the MT/MST is observed in deaf individuals relative to hearing controls ( Bavelier et al., 2001 ; Fine et al., 2005 ). This pattern echoes a general trend in the literature, where the most significant population differences have been reported for motion stimuli in the visual periphery under conditions that engage selective attention, such as when the location or time of arrival of the stimulus is unknown or when the stimulus must be selected from distractors ( Bavelier et al., 2006 ). These findings suggest that deafness is associated with alterations in visual attention, resulting in changes in the recruitment of brain networks involved in the processing of visual information.

These apparently contradictory hypotheses highlight the necessity of organising previous research within a recognized model of attention. This review aims to respond to this need by systematically analysing the tasks employed to measure various aspects of attention in each study.

1.2 The integrative hypothesis

The contradictory results mentioned previously prompted an integrative review published by Dye and Bavelier (2010) . These authors proposed that while the deficiency hypothesis and enhancement hypothesis may appear to be mutually exclusive, the conflicting evidence concerning the impact of deafness on visual attention could arise from measuring different aspects of visual attention. Consequently, the deficit view is predominantly supported by studies focused on the allocation of attention over time, whereas the compensation view is backed by studies measuring the allocation of attention across space. Therefore, when considering different aspects of visual attention, a striking pattern of attentional enhancements and deficits emerges as a consequence of early deafness.

In addition, these two perspectives consider groups of different ages and backgrounds. Individuals in the deaf and hard of hearing population are quite diverse regarding their preferred mode of communication (sign language versus oral language), the age of acquisition of their native language, the hearing status of their parents, the aetiology of hearing loss (e.g., genetic, infection), and the implantation of cochlear implants [CI—a small electronic device that is surgically implanted into the inner ear to help provide a sense of sound to individuals with severe to profound hearing loss ( Wilson and Dorman, 2008 )]. Most of the research suggesting that deaf children have problems with visual attention has focused on deaf children learning spoken language, examining changes in sustained visual attention after restoration of auditory input through a CI ( Mitchell and Quittner, 1996 ; Smith et al., 1998 ; Quittner et al., 2004 ). In contrast, studies suggesting that the visual system compensates for the lack of auditory input by enhancing the monitoring of the peripheral visual field have primarily involved deaf adults. Specifically, these studies have focused on culturally deaf individuals born to Deaf parents, acquiring American Sign Language (ASL) as their first language and lacking CI. This group is compared to those who received oral speech therapy and have CI ( Bavelier et al., 2006 ; Dye et al., 2009 ).

Dye and Bavelier (2010) suggested that the deficiency and compensatory views were not necessarily contradictory but complementary in explaining the cross-modal reorganization of visual attention after early deafness. They propose an integrative view in which early auditory deprivation does not have an overall positive or negative impact on visual attention, but rather, selected aspects of visual attention are modified in various ways throughout the developmental trajectory.

However, this division of visual attention in temporal and spatial aspects is very broad, and the paradigms used to test these hypotheses have certain shortcomings. Studies examining the impact on temporal attention used measures from the Rapid Serial Visual Presentation Paradigms and the Attentional Blink; however, consistent results were not observed across different experiments ( Dye and Bavelier, 2010 ; Dye, 2014 ; Thakur et al., 2019 ). Concerning spatial attention, the Useful Field Of View (UFOV) task has been employed. However, this complex dual task requires following two instructions — to both detect and locate a target while ignoring several distractors. Consequently, working memory, inhibition, orienting, and divided attention can all be deployed in this task, giving rise to what is referred to as the task impurity problem ( Miyake et al., 2000 ).

1.3 The attention networks model

Understanding the potential deficits and enhancements in visual attention among deaf individuals requires recognizing that visual attention is not a unitary entity. From this perspective, based on behavioral and neuroscientific studies, Posner and colleagues have suggested a model that divides the human attentional system into three functionally and anatomically independent networks responsible for alerting, orienting, and executive attention ( Fan et al., 2002 , 2005 ; Posner and Rothbart, 2007 ; Petersen and Posner, 2012 ). As already mentioned, previous hypotheses suggest that various aspects of visual attention can be affected differently in deaf individuals due to compensatory changes. The attentional networks model offers a framework to measure these different changes by separating attention into several functions.

The alerting network is responsible for achieving and maintaining a state of elevated sensitivity to incoming information. Alertness can be further subdivided into tonic and phasic alertness (for a review, see Sturm and Willmes, 2001 ). Tonic alertness (also called vigilance or sustained attention) is a state of general wakefulness or vigilance and refers to the ability to sustain attention over a period of time. Phasic alertness is a more transient alert state, modulated by a warning that precedes a target stimulus and prepares the individual for a fast reaction. Performance within this network has been measured using tasks where the appearance of the target is preceded by an anticipatory alerting cue, provoking a phasic change in alertness. This transition involves a shift from a resting state to a prepared state, ready to detect and respond to an expected event ( Marrocco and Davidson, 1998 ; Beane and Marrocco, 2004 ). Tonic alertness, on the other hand, is typically evaluated through lengthy and repetitive tasks requiring participants to identify and respond to infrequently occurring targets, the most frequent example being CPTs ( Petersen and Posner, 2012 ).

The orienting network is responsible for the movement of attention throughout space, allowing the selection of specific information from numerous sensory inputs. In this regard, orienting can be reflexive ( exogenous ), such as when a sudden target event draws attention to its location, or it can be voluntary ( endogenous ), such as when a person searches the visual field looking for a target ( Jonides, 1981 ). Although overt orienting is often associated with head or eye movements toward the target, it can also enhance target processing by covertly orienting attention ( Posner, 1980 , 2016 ). Spatial orientation has traditionally been studied with tasks based on the “spatial orienting paradigm” or “cost and benefits paradigm.” In these tasks, the participants are presented with a fixation point and placeholders (the location where the target appears) at both sides of a fixation point. Following the onset of the fixation point, an attentional cue is presented, followed by the target to which participants must respond. Trials are categorized as cued/valid if the target appears at cued locations, uncued/invalid when it appears opposite to the cue, or neutral when the cue appears at the centre or both locations. In typical measures of exogenous orienting, a change occurs in the placeholder location to elicit an involuntary orienting response (such as the illumination of the locations). Conversely, in measures of endogenous orienting, a central cue is presented to prompt a voluntary orienting response toward a specific location or object ( Uncapher et al., 2011 ; Chica et al., 2014 ).

Finally, the executive attention network involves more complex mental operations to detect and resolve the conflict between expectation, stimulus, and response. While this network shares some overlap with executive functions, it specifically involves processes related to planning and executing goal-directed actions. However, executive functions are a more general domain that includes working memory, mental flexibility, conflict monitoring, and, in close association with executive attention, inhibitory control ( Botvinick et al., 2001 ; Matsumoto and Tanaka, 2004 ). Assessment of the executive attention network typically involves “resolution of conflict” paradigms, which require the suppression of either processing or responding to information that elicits incorrect or inappropriate responses ( Posner and DiGirolamo, 1998 ). Examples of such paradigms include the flanker ( Fan et al., 2002 ), Stroop ( Fan et al., 2003 ), or Simon tasks ( Simon and Craft, 1970 ).

One commonly used task specifically designed to measure most of these networks is the attention network test (ANT), which is based on two paradigms — the flanker task and the cost and benefits paradigm. The ANT enables the evaluation of three attentional networks in children and adults: phasic alerting, exogenous orienting, and executive attention ( Fan et al., 2002 ).

The main task is based on the flanker paradigm where the participant must press two keys indicating the direction (left or right) of a central arrow surrounded by congruent, incongruent, or neutral flankers. The difference in reaction times or accuracy between the congruent and incongruent conditions provides a measure of the executive attention network. The efficiency of the alerting network is examined by changes in performance resulting from a warning signal preceding the target, compared to trials without any previous cue. The efficiency of the orienting network is measured by comparing the performance benefits associated with a spatial cue predicting the location of the stimulus array (above or below fixation) with a central cue.

The integrative hypothesis proposed by Dye and Bavelier (2010) predicts that the strengths and weaknesses in visual attention resulting from early auditory deprivation are also linked to the abilities of orienting, alerting, and executive functions within the visual attention networks model developed by Petersen and Posner (2012) . Consequently, it is important to identify the tasks used to measure attention in deaf individuals and their possible interpretation according to the attention networks model. Understanding the weaknesses and strengths of visual attention networks related to early auditory deprivation aids in characterizing the developmental trajectory of these attentional functions during middle childhood (from 6 to 12 years old) since this is an important developmental stage for visual attention ( Rueda et al., 2004 ) and marks the beginning of formal schooling.

1.4 Objectives

To our knowledge, no systematic review has included evidence regarding the integrative hypothesis proposed by Dye and Bavelier (2010) . Furthermore, since the publication of the 2008 review by Tharpe and colleagues, no comprehensive review has been conducted to gather research findings enabling the identification of visual attention functions that could be diminished or enhanced in individuals with early auditory deprivation.

We conducted a systematic review of studies published between 2008 and 2023 focusing on deaf populations (from middle childhood through adulthood). The objective was to analyse investigations exploring one or more visual attention functions described in the attentional networks model. More specifically, our systematic review aims to:

1. Determine the most frequently studied functions of alerting, orienting, and executive attention in deaf individuals, along with the task paradigms employed to investigate such functions.

2. Identify the main strengths and impairments observed in the functioning of attentional networks in deaf adults and explore whether differences are found depending on the use of different communication systems, cochlear implants, and age of cochlear implant acquisition.

3. Examine the key developmental changes observed in the functioning of attention networks in deaf children during middle childhood (ages 6–12) and identify the main differences compared to typical hearing children of the same age.

2.1 Search strategy

We conducted a search on October 9th, 2023, of the peer-reviewed literature published in English between 2008 and 2023. The search was carried out on the Web of Science, Medline, Scielo, and Psycinfo databases, focusing on experimental studies of deaf populations aged 6–50 years. Using performance tasks to measure visual attention. The search utilized specific terms with relevant connectors to target visual attention measures and the population of interest. The search terms included: (deaf* OR “auditory deprivation” OR “hearing impairment”) AND (“orient*” OR “alert*” OR “spatial attention” OR “attention network” OR “visual selective attention” OR “visual attention” OR “sustained attention” OR “altered attention” OR “divided attention” OR “visuospatial attention” OR “executive attention”). Data extraction adhered to the recommendations provided by the Cochrane group ( Higgins and Green, 2011 ) and the Preferred Reporting Items for Systematic Review and Meta-Analyses protocol (PRISMA; Moher et al., 2009 ).

2.2 Selection criteria

We use the PICOS strategy to define inclusion criteria (Participants, Intervention, Comparisons, Results, and Studies). This review includes studies with the following characteristics: (P) participants without a psychiatric history and typical neurodevelopment with mild, severe, or profound bilateral deafness aged between 6 and 50 year; (I) measures of some of the specific functions of the attention networks, including alerting orienting and executive attention. No specific intervention is considered in this review; (C) Transversal studies comparing performance between the deaf and typical hearing population, studies that compare the deaf population across different clinical variables such as CI and system of communication, and longitudinal studies within the deaf population assessing the development of visual attention; (O) studies are included where at least some of the attention networks can be separately measured through performance-based tasks based on the previously mentioned paradigms; and (S) Single case studies, doctoral theses, conference presentations, and papers without peer review are excluded.

2.3 Data extraction and quality evaluation

The initial search yielded 2,603 articles. After excluding duplicates between databases, 1,349 articles were removed. After applying the exclusion criteria, the studies were filtered by title and abstract, resulting in 86 remaining papers by the first author. The full texts of these 86 articles were then read and analysed by all authors. Most articles were excluded due to the inclusion of populations with other deficits, non-performance-based measures, or tasks that measured other aspects of visual attention not included in the attention networks model. In total, 24 articles met our inclusion criteria in agreement with all authors (see Figure 1 ).

Figure 1 . Flow chart of the identification, screening, eligibility, and selection of studies.

Based on our research objective, the articles were classified according to the age of the participants: individuals aged 18 to 60 were categorized as adults, while those aged 6 to 12 were considered children. After some deliberation among the authors, studies involving participants up to 14 years old were included in the children category, along with a study by Kronenberger et al. (2013) which encompassed individuals aged 7–25 years. Significant statistical differences between deaf or hard of hearing and fully hearing individuals in measures assessing attention network efficiency were used as an indication of specific outcomes for each study.

The risk of bias was assessed for all articles using the Newcastle-Ottawa scale (NOS; Wells et al., 2021 , adapted from Herzog et al., 2013 ) to evaluate the quality of the studies. In this version, the quality scores were based on the selection of sample, comparability between groups, and the measurement of results. For cross-sectional studies, a maximum score of 10 can be obtained, with a score above 6 considered a satisfactory methodology score ( Orton et al., 2014 ). In this systematic review, none of the studies included in the final analysis scored <7 (see Table 1 ).

Table 1 . Risk of bias scores adapted from the Newcastle-Ottawa scale.

3.1 Frequency of studies and tasks used

The initial objective of the study was to determine the most frequently studied aspects of attention. Of the 24 included studies, 23 adopted a cross-sectional experimental design and one was a longitudinal study. Additionally, 15 studies focused solely on adult samples, eight studies exclusively involved children, and one study included both adult and child participants. Not all studies investigated a single attention network (see Table 2 ).

Table 2 . Studies included in the review by group of age sample and function measured.

3.1.1 The alerting network

The alerting network was studied in 8 of 24 articles. Among these studies, five exclusively involved children aged between 6 and 12 years, two studies focused on adults aged between 19 and 57, and one study used a mixed sample of adults and children aged between 7 and 25. Except for two of the 11 studies ( Daza and Phillips-Silver, 2013 ; Bharadwaj et al., 2020 ), the rest compared the deaf group with their hearing peers. Six of the 11 studied the tonic alerting network using CPTs, while one studied phasic alerting using the ANT (see Table 3 ).

Table 3 . Paradigms used in the studies included in the review.

As mentioned above, CPTs are frequently used to measure visual attention in deaf individuals. Depending on the paradigm used, several interpretations are possible regarding the specific function measured. Following the previously described example of the GDS, commission errors due to responding to “9” when no “1” appeared are considered impulsive, lack of response or omission errors are considered distraction/inattention, and the most commonly used “ d ’” combines commission and omission errors to obtain a measure of sensitivity and is considered to show vigilance, which is why it has been classified as a tonic alerting measure ( Baijot et al., 2013 ).

3.1.2 The orienting network

The orienting network was studied in 12 of the 24 articles. Only two studies focused on children, one involving a sample aged between 6 and 14 years and another involving both children and adults aged between 10 and 58. The majority of studies (seven out of 12) were conducted exclusively with adults aged between 18 and 57. In eight out of 12 articles, exogenous orienting was studied, using spatial orienting paradigms, including the ANT. Four articles investigated endogenous orienting using spatial orienting paradigms. A visual search paradigm designed by Heimler et al. (2015a) allows for obtaining a measure of exogenous and endogenous orienting and was included in both categories (see Table 3 ).

As mentioned previously, the orienting paradigms facilitate the measurement of exogenous and endogenous orienting by manipulating cues before the appearance of targets. These paradigms provide various measures of the orienting process, the most common being the facilitation of a valid cue toward the target. Additionally, they can be used to measure the disengagement of attention following an invalid cue. In cases where eye movements are considered, overt orienting of attention is measured instead of covert attention. Four of the nine studies focusing on exogenous attention with orienting paradigms measured saccadic eye movements (overt attention), while the remaining five used only manual responses (covert attention). Heimler et al. (2015a) designed a visual search paradigm in which participants must search for a target (tilted line) among a visual field full of similar distractors (straight lines) while ignoring a salient distractor (line tilted opposite direction). The salience of the target and distractor was manipulated trial by trial by changing their colors. This approach was driven by the idea that the salient stimulus attracts exogenous attention while the target requires an endogenous search across the visual field. Through this method, they were able to obtain a measure of endogenous orienting and exogenous orienting.

3.1.3 The executive attention network

The executive attention network was studied in 7 of 24 articles. Four studies involved a sample of children aged between 6 and 13 (see Figure 2 ), while three focused exclusively on adults aged between 18 and 58 (see Figure 3 ). Three of the 7 used conflict tasks with several modifications, three used the ANT, and the remainder employed the modified CPT developed by Dye and Hauser (2014) (see Table 3 ).

Figure 2 . Number of studies with deaf children in each attention network function and the general findings in comparison to full hearing children. *Deficits in executive attention found with younger children [2, 74].

Figure 3 . Number of studies with deaf adults in each attention network function and the general findings in comparison to full hearing adults. *Enhancements found in overt orienting but not in covert orienting and deficits with executive attention found only during specific conditions.

Regarding measures of executive attention, paradigms classified as conflict tasks were included. These tasks require participants to ignore distractors while attending to a central target. Notably, the study conducted by Dye and Hauser (2014) used a CPT but compared the execution of a CPT with and without distractors in the same sample, thereby measuring executive attention.

3.2 Comparisons between deaf and hearing adults

Our second objective was to compile the differences found between deaf and full hearing adults. We note that all studies involving adults employed a cross-sectional design (see Figure 2 ). The two studies that measured tonic alerting in deaf adults revealed poorer performance compared to hearing peers when using CPTs as a measure ( Kronenberger et al., 2013 ; Bharadwaj et al., 2020 ). Specifically, Kronenberger et al. (2013) used the Test of Variables of Attention (TOVA), indicating poorer performance by deaf individuals across all measures. Similarly, Bharadwaj et al. (2020) used the Integrated Visual and Auditory Continuous Performance Test (IVA plus CPT), demonstrating that deaf individuals commit more omission errors and have slower reaction times.

The only study that measured phasic alerting with alerting cues found an advantage in deaf adults ( Prasad et al., 2022 ). Deaf adults also seem to have advantages in covert exogenous orienting ( Xingjuan et al., 2011 ; Brazão et al., 2021 ; Li et al., 2022 ; Prasad et al., 2022 ). However, studies that measured overt attention with saccadic movement found no facilitation of exogenous orienting with this measure ( Bottari et al., 2012 ; Prasad et al., 2015 ; Heimler et al., 2015a ; Jayaraman et al., 2016 ). The five studies that measured endogenous orienting found no differences between deaf and full-hearing adults ( Bottari et al., 2008 ; Heimler et al., 2015a , b ; Bonmassar et al., 2021 ; Li et al., 2022 ).

Regarding executive attention, no differences were found between deaf adults and their hearing peers in a typical flanker task ( Holmer et al., 2020 ). Chen et al. (2010) used a paradigm with three conditions: congruency, the distance of the distractor (central or peripheral), and screen proximity (typical computer screen or projected onto a wall) and found that deaf adults showed greater interference from peripheral distractors compared to central cues. This effect was reversed when the display was projected onto a wall. Hauthal et al. (2012) designed a paradigm where participants had to discern the gender of a central target while faces appeared as distractors at the flanks. The faces could either match or differ in gender from the target, creating interference. The study revealed that with a high volume of distractors, adult deaf signers without CI still showed interference effects while hearing adults did not.

Regarding our secondary objective, to explore any differences observed among deaf individuals in relation to variables concerning hearing loss history, device use and mode of communication, very few studies examined adults with CI (see Table 4 ), possibly due to the relative novelty of the technology ( Wilson and Dorman, 2008 ). The few studies that included adults with CI did not find any effect of implantation in tonic alerting ( Kronenberger et al., 2013 ; Bharadwaj et al., 2020 ). The rest of the findings will be discussed below along with the results of studies in children.

Table 4 . Basic deaf related variables regarding auditory access and system of communication.

3.3 Development of attention networks and comparison between deaf and full hearing children

With respect to our third and final objective, we found one longitudinal study and four studies that either compared groups across different ages or treated age as a continuous independent variable. In deaf individuals, tonic alerting was observed to develop between 6 and 13 years of age ( Dye and Hauser, 2014 ; Dye and Terhune-Cotter, 2023 ). With exogenous orienting, the only result found was that the fundamental operations of moving and engaging develop from 6 to 7 years of age ( Daza and Phillips-Silver, 2013 ). Lastly, executive attention appears to develop around 8 years of age in deaf individuals ( Dye and Hauser, 2014 ). As mentioned before, comparisons between differences between individuals with and without CIs and different systems of communication were almost exclusive to studies with children. When comparing deaf and typical hearing children, greater challenges in tonic alertness were evident in speaking deaf children with CI ( Yucel and Derim, 2008 ; Hoffman et al., 2018 ), but not in deaf signers without CI ( Dye and Hauser, 2014 ). Regarding phasic alertness, Daza and Phillips-Silver (2013) found a greater alerting effect in the ANT when comparing oral deaf children with CI and deaf signers without CI. Daza and Phillips-Silver (2013) also found faster movement and engagement in a spatial orienting paradigm when comparing deaf signers without CI to oral deaf children with CI. However, in endogenous orienting, an advantage was found in deaf children (independent of the system of communication) when a social central cue was employed ( Pavani et al., 2019 ). When measuring executive attention with a flanker task, no differences were found between deaf children (mostly speaking with CI) and hearing children ( Daza and Phillips-Silver, 2013 ; Daza González et al., 2021 ) except for Merchán et al. (2022) who observed poorer performance in deaf children. Dye and Hauser (2014) , examining the effect of distractors on a central target with a focus on the difference in performance on two CPTs, found that deaf signers without CI showed poorer performance than their full hearing counterparts.

4 Discussion

4.1 current frequency of studies and tasks used.

As observed, there exist notable gaps in our understanding of the visual attention network in deaf individuals, with research focusing on different functions depending on the age of the participants. While tonic alerting has been extensively researched in both adult and youth deaf populations, primarily through CPTs, the exploration of phasic alerting remains scarce in both groups. Notably, only one study in adults has investigated phasic alerting, emerging as an unexpected result from a cost and benefit paradigm measuring orienting behavior ( Prasad et al., 2022 ).

Similarly, concerning the orienting network, while there is a wide range of research on exogenous orienting in deaf adults, few studies have tested these differences in deaf children ( Daza and Phillips-Silver, 2013 ). Moreover, endogenous attention has been underexplored in both age groups.

Regarding executive attention, there appears to be a more balanced interest across developmental stages, primarily through flanker tasks in children and a broader range of conflict tasks in deaf adults. This is likely due to the fact that flanker tasks have been previously studied in deaf adults prior to the scope of this review ( Sladen et al., 2005 ; Dye et al., 2009 ).

From these observations, it becomes evident that there is a critical need to delve deeper into the exploration of phasic alerting and endogenous orienting of attention, particularly in deaf and hard of hearing children. This need arises from the potential existence of adaptive developmental aspects in visual attention that warrant further investigation.

4.2 Results of comparisons between deaf and hearing adults

The results in deaf adults seem to indicate a deficit in the tonic alerting network, which can be explained by several hypotheses. One possibility is that deaf individuals have difficulties in sustaining attention over time, possibly due to a more rapid depletion of attentional resources. To test this hypothesis, investigating how performance changes over the course of a task could provide insights into whether there is a faster decline in performance or a general difficulty in executing the task. While Hoffman et al. (2018) attempted to analyse this aspect, they focused exclusively on children, which will be discussed below. Another hypothesis emerges from the division of labor perspective, which supports the deficit view. According to this notion, the observed results may be due to the need for deaf individuals to rely on vision to simultaneously monitor their environment and focus on a specific task. This dual demand on attentional resources might limit the resources available for performing visual tasks such as the CPT ( Smith et al., 1998 ; Quittner et al., 2004 ).

Normally, phasic alerting is primarily dependent on the auditory system. Therefore, in adults, it would be reasonable to expect that adaptive mechanisms could lead to a heightened state of alert generated by visual cues, as demonstrated in the experiment conducted by Prasad et al. (2022) .

The overall advantage observed in spatial exogenous orienting in deaf adults appears to be attributable to covert orienting rather than overt orienting/ eye movements ( Prasad et al., 2015 ; Brazão et al., 2021 ; Prasad et al., 2022 ). This supports the notion of an adaptive alteration in the visual attention system in deaf individuals. This adaptation enables them to monitor the environment since they are able to efficiently shift their attentional focus across the visual field towards important stimuli and also disengage from them more rapidly.

The mechanisms governing orienting of attention or eye movements have been shown to be more dependent on endogenous attention, which could explain why the differences between deaf and full hearing individuals do not extend to the results of these tasks ( Zangrossi et al., 2021 ; Celli et al., 2022 ). Endogenous orienting does not differ between deaf and typical hearing adults, whether measured by visual search ( Heimler et al., 2015a ) or spatial orienting paradigms using central cues ( Heimler et al., 2015b ; Bonmassar et al., 2021 ; Li et al., 2022 ). One explanation for this result is that endogenous orienting of attention requires voluntary control of attention (top-down), while exogenous attention is an involuntary mechanism (bottom-up), as some results indicated that deaf individuals could have worse executive control, possibly explaining the lack of differences in these tasks ( Li et al., 2022 ). However, as we have found in this review, deficits in executive control are not common in adults or native signers, contrary to the results found in orienting. Another possible explanation for this discrepancy is that this function does not show differences since it is not inherently adaptative. In contrast, the improvements observed in exogenous orienting could stem from the need to monitor environmental changes using only the visual system, without the support of the auditory system. On the other hand, attention shifts due to endogenous attention could be distracting for deaf individuals required to maintain a strong focus on hands and facial expressions during conversations.

Regarding executive function, no differences were found in a typical flanker task ( Holmer et al., 2020 ). However, when distractors were placed in the periphery instead of the centre, deaf individuals showed poorer performance compared to their hearing peers ( Chen et al., 2010 ). These contradictory results seem to support the hypothesis that the observed performance deficits in conflict tasks with central targets may not necessarily be due to deficits in executive attention. Instead, these findings could be due to the further allocation of attentional resources towards distractors in comparison to hearing individuals. This explanation is further supported when these results are compared to those of the UFOV tasks, where both targets and distractors are located in the periphery. In these tasks, deaf individuals tend to have an advantage ( Dye et al., 2016 ; Samar and Berger, 2017 ). However, the findings of Hauthal et al. (2012) could indicate an adaptive change specifically in the processing of faces. These results suggest that the performance of signers without CI in executive attention tasks depends on the position of the target, which can be explained by the further allocation of attention towards the periphery. An alternative interpretation of these findings is that deaf adults may develop an advantage in the ventral attention network (VAN). The VAN is responsible for reflexive bottom-up attentional mechanisms and has been associated with exogenous orienting and phasic alerting This could potentially explain the observed benefits in both functions among deaf adults. In contrast, the dorsal attention network (DAN) governs voluntary or top-down attentional mechanisms and has been linked to endogenous orienting, tonic alerting, and executive functioning ( Corbetta and Shulman, 2002 ; Rueda et al., 2023 ). Apart from tonic alerting, it appears that deaf adults may not experience performance deficits relative to typical hearing controls in this pathway.

4.3 Findings of comparisons between deaf and hearing children

In children, the differences between deaf and typical hearing individuals vary according to age, suggesting that middle childhood is an important period of development for visual attention. Our review found that deaf children show worse scores in CPTs, which is argued as being indicative of a deficit in tonic alerting. However, contrary to this notion, Hoffman et al. (2018) found no differences in performance block by block between deaf and hearing children. This suggests that tonic alerting or vigilance may not be affected, but the difference in performance is due to the division of labor, as mentioned previously. Furthermore, the poor performance during these tasks was characterized by high commission errors ( Yucel and Derim, 2008 ; Hoffman et al., 2018 ), which could be interpreted as poor inhibition or impulsivity. These findings have been replicated with other paradigms that measure response inhibition, such as the Go/No Go or Simon tasks ( Figueras et al., 2008 ; Botting et al., 2017 ; Hall et al., 2018 ).

The results reported by Daza and Phillips-Silver (2013) , indicating higher phasic alerting and faster exogenous orienting, could potentially suggest a benefit due to the lack of auditory stimulation. However, these results have not been directly compared with those of hearing children. We must also consider that the differences in endogenous attention found by Pavani et al. (2019) can only be interpreted in the context of gaze cues, since there is evidence that other (non-gaze) directional cues rely on different processes ( Heimler et al., 2015b ). Consequently, there is insufficient experimental data on orienting in deaf children in comparison to their hearing counterparts, which prevents us from drawing any firm conclusions in this regard.

Concerning executive attention, discrepancies between the results of Dye and Hauser (2014) and Merchán et al. (2022) and those of Daza González et al. (2021) could be due to differences in the sample, specifically in terms of age, since the latter study focused on children aged 9 to 10 years. As observed in adults, deaf children show no difference in UFOV task performance between the ages of 7 and 10 years. In fact, their performance surpasses that of their hearing peers between the ages of 11 and 17 ( Dye et al., 2009 ; Dye and Bavelier, 2010 ). This discrepancy in performance might manifest as a reduced ability to ignore distractors when they are at the periphery and the target is in the centre of the visual field. Notably, this difference disappears when the target is also positioned in the periphery, supporting the hypothesis that attentional resources are allocated toward the periphery.

In general, we can conclude that, as expected, the findings have revealed improved performance of deaf individuals in tasks related to covert exogenous orienting, with limited impact on endogenous orienting in adults. However, deaf individuals show poorer execution of tasks involving tonic alertness and executive attention, except when the target is presented peripherally. These results are consistent with much of the clinical literature in deaf individuals ( Barker et al., 2009 ) and support the integrative hypothesis suggesting a deficiency in the temporal distribution of attention and an enhancement in spatial distribution ( Dye and Bavelier, 2010 ). Finally, from the perspective of the attention network model, our study highlights the need to further explore phasic alerting. Currently, there is a gap in research exploring differences in exogenous and endogenous orienting between deaf and full hearing children and a lack of studies investigating the endogenous orienting network in deaf adults.

4.4 Development of attention network functions in deaf children

Regarding our objective of characterizing the development of attentional networks in middle childhood within the deaf population, several conclusions can be drawn. However, we must consider the need for further research in this area, particularly through longitudinal studies.

Our findings indicate that tonic alertness continues to develop from ages 6 to 13 in both deaf and typical hearing children ( Dye and Hauser, 2014 ; Dye and Terhune-Cotter, 2023 ). This aligns with previous research on typical hearing children using the same task, which showed a specific development ceiling at 10 years old ( Betts et al., 2006 ). However, it appears that deaf individuals do not reach the levels observed in typical hearing adults, at least those who are not native signers ( Bharadwaj et al., 2020 ).

The elemental operations of moving and engaging improve between the ages of 6 and 7 in deaf children ( Daza and Phillips-Silver, 2013 ). In comparison to hearing children, our results suggest that orienting networks continue to develop during middle childhood in deaf individuals, whereas in their hearing counterparts, this development tends to plateau at around 6 years old ( Rueda et al., 2004 ; Pozuelos et al., 2014 ; Federico et al., 2017 ). Notably, this development in deaf individuals appears to extend into adulthood, providing them with an advantage over typical hearing adults. Interestingly, when measuring electrophysiological brain activity through evoked potentials, improvements in visual attention related to saliency processing and orienting of attention have been observed as early as 3 years of age. These measures demonstrate improvement during the early years in deaf children, indicating early and differential development of these components of attention ( Campbell and Sharma, 2016 ; de Schonen et al., 2018 ; Gabr et al., 2022 ; Corina et al., 2024 ).

Finally, executive attention seems to improve between 7 and 9 years of age in deaf children. Dye and Hauser (2014) found that deaf signers without CI reach the same levels of performance between 9 and 13 years old. However, Daza González et al. (2021) found no differences among children aged 9–10, while Merchán et al. (2022) observed worse performance in a sample of 7–10 years old. These findings are consistent with those reported in studies of typical hearing children, suggesting that difficulties found in this aspect of the attention network cannot be solely attributed to late development ( Rueda et al., 2004 ; Pozuelos et al., 2014 ; Federico et al., 2017 ). When comparing deaf and hearing adults, it is plausible that deaf individuals continue to show development in exogenous orienting during early childhood, eventually achieving better performance than their hearing counterparts ( Bottari et al., 2012 ; Prasad et al., 2015 ). In adulthood, deaf signers without CI reach similar levels in executive attention when central targets are present ( Chen et al., 2010 ; Holmer et al., 2020 ). However, differences in tonic alertness may persist into adulthood ( Parasnis et al., 2003 ; Kronenberger et al., 2013 ).

4.5 Effects of the communication system and the use of cochlear implants

In most studies, the use of sign language is associated with the absence of a CI. It is important to recognize the clear distinction between culturally deaf people who communicate mainly in sign language within deaf communities and those who have received CI along with speech therapy. The latter group has experienced some level of auditory input and uses a language that is less reliant on visual cues.

In adults, there are no studies on tonic alertness involving deaf signers without CI. However, age at CI implantation does not seem to have an impact on CPT performance ( Kronenberger et al., 2013 ; Bharadwaj et al., 2020 ). While no differences were observed between deaf signers without CI and full hearing children ( Dye and Hauser, 2014 ), differences have been found in oral-speaking deaf children with CI ( Yucel and Derim, 2008 ; Hoffman et al., 2018 ). Additionally, Daza and Phillips-Silver (2013) found differences in tonic alertness between oral speaking deaf children with CI and deaf signers without CI in favor of the former. Dye and Terhune-Cotter (2023) found that while the English language was a strong predictor of better sustained attention, ASL proficiency was a more accurate predictor of response inhibition.

Generally speaking, these findings suggest a consistent trend toward poorer performance on tonic alerting tasks in oral speaking deaf individuals. Notably, the lack of an effect of age of implantation in adults raises the possibility that early language acquisition does not influence these outcomes. Regarding exogenous orienting, it is evident that elementary operations of orienting such as moving and engaging are enhanced in deaf signers without CI compared to oral speaking deaf individuals with CI ( Daza and Phillips-Silver, 2013 ). Additionally, the advantage observed in executive attention towards peripheral targets in adults appears to be more prevalent among deaf signers without CI ( Samar and Berger, 2017 ), while in children these improvements have also been found in deaf signers without CI ( Dye et al., 2009 ).

These findings align with the main hypothesis put forward to explain differences in performance on tasks that measure different executive functions in deaf people and could also be applied to these results, that is, worse performance can be attributed to late acquisition of language ( Hall et al., 2017 , 2018 ; Merchán et al., 2022 ). This explanation has commonly been invoked when attempting to explain performance on executive function tasks, but as observed in this review, tonic alertness also appears to be affected. However, an adaptive form of development is evident when executive attention is directed toward the periphery in deaf signers without CI who lack auditory stimulation and have delayed acquisition of language ( Dye et al., 2009 ; Samar and Berger, 2017 ). Unfortunately, there is insufficient evidence to conclusively establish the impact of these variables on phasic alertness, endogenous orienting, and executive attention.

5 Conclusion

In summary, there are notable gaps in the literature regarding the functions of visual attention networks, specifically in the alerting network functions in adults, phasic alerting, and both orienting networks in children. Current evidence suggests that deaf adults show poorer performance during CPTs, but this might not necessarily be attributed to deficits in tonic alerting. Phasic alerting, on the other hand, appears to confer advantages in deaf adults. Exogenous orienting shows enhancements, whereas endogenous orienting does not. Additionally, differences in executive attention are evident, particularly depending on the peripheral placement of the distractors. In children, the evidence reveals similar patterns of results, with the exception that difficulties in executive attention are observed before the ages of 9 or 10.

Regarding individual differences in language delay and the use of CI, it seems that benefits in exogenous orienting are more frequent in deaf individuals without CI and users of sign language while language abilities appear to be a good predictor of difficulties in executive attention. This understanding contributes to the growing body of knowledge in the field, emphasizing the need for further research to bridge the identified gaps and refine our comprehension of the intricate development of visual attention networks in the deaf population.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Author contributions

NG: Writing – original draft, Methodology, Investigation. JP-S: Supervision, Conceptualization, Writing – review & editing. MD: Writing – original draft, Supervision, Writing – review & editing, Funding acquisition, Conceptualization.

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This research was supported by a grant PID2019-111454RB-I00/AEI/10.13039/501100011033 from Spanish Ministry of Science and Innovation—Spanish State Research Agency, to the last author.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

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Keywords: deaf, children, attention, hearing, orienting, review methodology, investigation

Citation: Gioiosa Maurno N, Phillips-Silver J and Daza González MT (2024) Research of visual attention networks in deaf individuals: a systematic review. Front. Psychol . 15:1369941. doi: 10.3389/fpsyg.2024.1369941

Received: 13 January 2024; Accepted: 22 April 2024; Published: 09 May 2024.

Reviewed by:

Copyright © 2024 Gioiosa Maurno, Phillips-Silver and Daza González. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: María Teresa Daza González, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Psychopharmacology

Whistleblowers and medical fraud: a book review, a new book on the history—and price—of exposing corruption in medical research..

Updated May 15, 2024 | Reviewed by Michelle Quirk

• What Is Psychopharmacology?
• Find counselling near me
• In medicine, whistleblowers face institutional denial, stonewalling, retaliation, and other kinds of reprisal.
• They expose coercive recruitment practices, conflicts of interest, weak protocols, and missing consent.
• In revisiting some of medicine’s worst scandals, a new book details the efforts taken to block accountability.

“Nobody should indulge in the fantasy that they will be celebrated for blowing the whistle,” warns Carl Elliott in his riveting new book, The Occasional Human Sacrifice: Medical Experimentation and the Price of Saying No, published today by Norton. “It is more likely that they will be vilified, forgotten, or both.”

The more than half-dozen cases detailed in his investigation bear out that message with telling regularity. Whether from institutional denial , stonewalling, protection, retaliation, or other kinds of reprisal, whistleblowing in medicine is shown to carry a high risk of failure. Those seeking accountability are often the only ones to face any consequences, and they can be severe: demotion or job loss, hefty legal fees, unwanted notoriety, and a strong risk of being disowned by one’s coworkers.

“It's a demoralizing book,” Elliott tells me when I request an advance copy, “but, well, that’s what the subject demanded.” It does. The scale of injury detailed in each chapter—coupled with extensive evidence from archives and local media—is as daunting as are the many efforts by institutions to deny error and responsibility.

Even more tawdry are examples where the culpable feign unjust persecution, claiming that they are the real victim—of a witch-hunt or smear campaign. On several occasions, the fervor of denial is enough to persuade oddly incurious review boards and regulatory agencies that the malpractice is sound, even that the work merits praise and prizes (in one case, a Nobel).

Meanwhile, those driven to expose the fraud—whether of coercive recruitment practices, glaring conflicts of interest, failure to establish informed consent, or vague protocols and missing control groups—can end up fired, discredited, and rejected. “What we do essentially,” a manager concedes, “is put [the colleague] in a little boat, tow it out to sea, and cut the rope. We never think about [them] again.”

“I felt an antipathy against me,” one employee recalls after a well-considered decision to take his findings to the agency empowered to investigate them. “They feared I was opening my mouth too wide.”

Another is berated for confirming that two patients had recently died on the study protocol, a harbinger of dozens more: “Who the hell are you to question what we do around here?” A third remembers, “Everyone at work looked at me like I was a cobra. I couldn’t have been more alone if they put me in the toilet.”

While revisiting some of medicine’s worst scandals—examples include four decades of intentionally untreated syphilis in hundreds of African-American men, a hepatitis experiment on dozens of intellectually disabled children, a years-long series of deadly total body irradiation experiments involving the federal government, even a cover-up of egregious fraud at the same institute in Sweden that awards the Nobel Prize in medicine—Elliott provides nuanced portraits of each whistleblower, including their motivation and psychology.

Invaluably, Elliott ends up amplifying a larger theme of institutional cowardice in the face of well-evidenced corruption. One whistleblower marvels of his former coworkers, “It was astounding that nobody gave a damn,” even about a study associated with high rates of death. Others are baffled that so many peers and reviewers uncover the fraud but do nothing about it, asking: “How do you stand by and let these things happen?”

Atypical Antipsychotics and Forced Consent

Prefacing each example of medical malpractice is Elliott’s gripping account of his own seven-year ordeal after reporting on a research scandal at his home university, where for 11 years he had taught ethics in its medical school. In May 2003, the university’s Department of Psychiatry oversaw the study of second-generation antipsychotics that included a shockingly violent suicide . As reported by “Side Effects” in 2009 after further details were reported by a local newspaper, the patient had been enrolled in the study over the stated objections of his mother, since he was then in the midst of a full-blown episode and might pose a risk to himself or others. Elliott elaborates:

The study in which Markingson died was funded by the pharmaceutical company AstraZeneca and designed to test its antipsychotic drug Seroquel. The study was marked by alarming red flags: conflicts of interest, financial pressures to get subjects into the study, a locked psychiatric unit where severely ill patients were targeted for recruitment. Most disturbing of all were the conditions under which Markingson was enrolled.… Not only was [he] psychotic when he signed the consent form, he was under a civil commitment order that legally required him to obey the recommendations of his psychiatrist. His mother wanted him to have nothing to do with the study. [The study leader ] enrolled Markingson anyway.

Further investigation unearths a disturbing number of malpractice cases in the same department: a nonconsensual addiction experiment on illiterate Hmong opium addicts, the injuries or deaths of 46 mentally ill patients under the care of a different faculty member. The professor leading the study in which Markingson died previously led a study on an experimental antipsychotic that, too, became associated with intense suicide ideation, previously unremarked. In that case, the patient managed to drop out of the trial, avoiding further risk of self-harm .

The reporting and investigation that Elliott felt compelled to pursue end up involving years of university stonewalling. Relations with even supportive colleagues sour. The intervention leads, eventually, to Senate hearings, an external review that faults the university’s oversight program and the passage of a new law in Minnesota meant to raise standards in medical research. But it generates no formal apology to Markingson’s mother. What she receives instead is a bill for legal fees sent by the same university that failed to sanction the forced participation of her son in a problematic clinical trial, even as it resulted in his death.

When Whistleblowing Backfires

This is the type of maddening pattern that repeats throughout The Occasional Human Sacrifice . Publicly stated concerns about misconduct are shown to backfire, sometimes spectacularly, leading to the demotion and discrediting of previously valued colleagues. In the process, review boards and sponsoring departments end up sullied and compromised—silent accomplices to malpractice—even as they may spend years fighting the charges and proclaiming the exposure to be the only cardinal sin.

The brilliance of Elliott’s book lies in the lessons it draws from overlooked detail. In the infamous Tuskegee, Alabama, experiment by the U.S. Public Health Service on hundreds of poor Black men with syphilis, where the agency “used free meals and burial insurance to lure them into an experiment in which they would receive no treatment for [the] potentially deadly disease,” the detail is that “ very few employees of the health service … saw anything wrong with this .”

The experiment ran for 40 years and took another seven to bring fully to light: “The public health establishment fought [discovery] at every turn. When the study was finally exposed, the federal government resisted paying for medical treatment for the victims. Another twenty-five years passed before the government apologized.”

“I think there is a ‘there’ there that we just maybe didn’t want to see,” an investigator tells Elliott of the staggering institutional blindspots that recur throughout, especially when reputations and significant funds are at stake. Concerning efforts to shield yet another study from investigation, Elliott adds: “It wasn’t just that they were unhappy to see their dirty laundry aired in public. Many of them didn’t think the laundry was dirty.”

“The force of social conformity is especially powerful in institutions that are driven by a sense of moral purpose,” notes Yale social psychologist Irving Janis, who is quoted in the book. “In academic health centers, that moral purpose is embedded in the dogma that medical research saves lives.”

“Since our groups’ objectives are good,” Janis continues, characterizing what the participants are said to feel, “any means we decide to use must be good.”

Elliott, C. (2024). The Occasional Human Sacrifice: Medical Experimentation and the Price of Saying No. New York: Norton.

Christopher Lane, Ph.D., is a Professor Emeritus of Medical Humanities at Northwestern University.

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Increased Screen Time as a Cause of Declining Physical, Psychological Health, and Sleep Patterns: A Literary Review

Vaishnavi s nakshine.

1 Department of Public Health Sciences, Jawaharlal Nehru Medical College, Datta Meghe Institute of Medical Sciences, Wardha, IND

Preeti Thute

2 Department of Anatomy, Jawaharlal Nehru Medical College, Datta Meghe Institute of Medical Sciences, Wardha, IND

Mahalaqua Nazli Khatib

3 School of Epidemiology and Public Health, Jawaharlal Nehru Medical College, Datta Meghe Institute of Medical Sciences, Wardha, IND

Bratati Sarkar

4 Department of English, Jawaharlal Nehru University, Delhi, IND

Dependency on digital devices resulting in an ever-increasing daily screen time has subsequently also been the cause of several adverse effects on physical and mental or psychological health. Constant exposure to devices like smartphones, personal computers, and television can severely affect mental health- increase stress and anxiety, for example, and cause various sleep issues in both children as well as adults. Risk factors for obesity and cardiovascular disorders, including hypertension, poor regulation of stress, low HDL cholesterol, and insulin resistance are among the physical health repercussions we see. The psychological health effects comprise suicidal tendencies and symptoms of depression which are associated with digital device dependency, screen-time-induced poor sleep quality, and content-influenced negativity. Oftentimes it can cause the induction of a state of hyper-arousal, increase stress hormones, desynchronize the body clock or the circadian cycle, alter brain chemistry and create a drag on mental energy and development. With a focus on brain development in children and detrimental effects in both adults and children, this research article goes on to explore the various aspects of screen addiction and excessive screen exposure.

Introduction and background

Digital devices and online spaces, above all, are considered one of the fundamental aspects of the existence of this current generation. Rapid advancements in technology make it possible for consumers in any part of the world, regardless of age, to experience a wider variety of fast-acting stimuli that are available with similar accessibility, practically anywhere via mobile devices, enticing them to indulge in the use of screens for longer than the suggested two-three hours per day. Computers, phones, and tablets- the heralds of easy-to-use internet hosts- have seen increased purchase and usage in the present times, which has significantly reduced the distance that had once separated everything and instead turned the world into a community resembling a global village. Undoubtedly, individuals-cum-residents of this same global village have been spending an excessive amount of their time online, which has both positive as well as negative consequences, both short- and long-term. While the usage of the internet as a whole is rising, unnecessary and troublesome use of the internet has reached medically alarming levels, too. Numerous reports have highlighted the detrimental effects of its usage, such as issues that affect one's sleep, mood, and communal interactions [ 1 ]. Internet addiction (IA) is turning out to be a severe general health problem across various nations on various continents, including ours, i.e., Asia. It has been proven that one of the multiple reasons for more and more individuals being affected by depression and feeling further isolated is their addiction to mobile phones and other digital gadgets, their dependency on the presence of people on the internet, their views and values, which need not be the individual’s own. It increases dependence on validation from faceless people on the internet. It reduces the rate at which one physically interacts with others in real life, which also affects the release and maintenance of adequate doses of feel-good hormones like dopamine, serotonin, endorphins, and oxytocin, which are naturally required by all. Overuse of digital media is thought to be a significant drawback in the development of healthy psycho-physiological resilience [ 1 ]. FOMO (Fear of missing out) has also been identified as a risk factor for binge usage of the internet. The relationship between FOMO and internet usage has been extensively researched in recent studies, with younger persons more prone to the risk of the same. Along with the detrimental effect on mental health, excessive screen time is also responsible for multiple physical health deteriorations [ 1 ]. 

Effects on sleep

The use of digital media is thought to interfere with sleep in subsequent ways:

Displacing Other Activities

Screen time can replace time spent on performing physical activities, which are directly beneficial for sleep every night [ 1 ].

Time of Use

Exposure to blue and intense light in the evening and at night from self-luminous devices may prevent melatonin from being produced, alter its timings of production and retention, and thus disturb the circadian rhythm. Moreover, prolonged texting post-bedtime is likely to shorten high school kids' sleep cycles, resulting in daily drowsiness and subpar academic performance [ 1 ].

Small touch screens, contrary to TVs, might send audible notifications during sleep time, delaying or preventing sufficient sleep. Consequently, it was observed that 18% of teenagers reported being awakened by their cell phones at least a few times throughout the night [ 1 ].

Media Content

Teenagers that use the internet more frequently have lesser durations of sleep, delayed bedtimes and wake-up times, and more daytime fatigue [ 2 ]. Those accessing social networking sites at night are more likely to sleep poorly, particularly if there is emotional involvement in the same. Additionally, engaging in an exciting task while staring at a luminous cell phone screen may enhance psychophysiological arousal, disturbing sleep [ 1 ]. The duration of time which is devoted to social media also affects how much and how well one sleeps, and good sleep is essential for academic success [ 3 ]. In 2011, Espinoza and colleagues polled 268 young adolescents specifically about social media and discovered that 37% said they had trouble sleeping due to the use of social networking sites. Adolescents use social media for 54% of their internet time. As we know, social media entails incoming alerts at all hours of the day, unlike conventional internet usage. This distinct social media characteristic is fundamental to the quality of sleep for a couple of causes [ 4 ]. First of all, because 86 percent of teenagers sleep in bedrooms with their phones nearby, frequently in their hands or shoved under their pillows, notifications at night time have the ability to disrupt sleep. They have also reported being awakened by incoming text messages and face problems in sound sleeping which are probably caused by social media [ 5 ].

Moreover, FOMO (Fear of Missing Out) is exacerbated by continual notifications, which seems to place a significant amount of pressure on people to be online all the time. Individuals mention feeling pressured, overwhelmed, and guilty if they are unable to respond to a text right away and that they face a great deal of anxiety whenever their access to messaging becomes constrained. Hence, it's likely that young people have trouble unwinding before bed because they worry about losing out on new texts or material. These special features of the usage of social media give us yet another cause to anticipate a connection between it and bad sleep [ 3 ]. A stronger correlation with specific usage of the internet at night time would suggest that exposure to digital screens before sleeping may disrupt circadian rhythms or cause sleep disruptions from notifications [ 5 ].

In contrast, a relationship between inadequate sleep and emotional involvement on the internet, specifically social media, would imply that an individual's difficulty unwinding before the night is caused by anxiety over missing out on fresh information and their inability to relax and calm down [ 6 ]. Even young children who are subjected to night-time media consumption have considerably lower sleep durations than those who are not engaged with night-time screen media [ 7 ]. The stimulating content and inhibition of natural melatonin by blue light produced via screens are two primary mechanisms underpinning the above connection. Furthermore, a persistent online presence disrupts sleep habits, that in turn influences mood [ 1 ]. Last, but not least, those who tend to spend more time online have a higher mental workload due to multitasking, increased levels of stress, and comparatively poorer quality as well as quantity of sleep, all of which are related to the deteriorating state of health [ 3 ]. Location

Teenage media device ownership is linked to earlier bedtimes and shorter sleep duration, relatively high bedtime resistance, with increased levels of sleep disruption, especially when the devices were kept in the bedroom [ 1 , 8 ].

Light Is Perceived as Electromagnetic Radiation

The occurrence of sleep during the night and the production of pineal melatonin coincides, indicating a significant link between the two processes [ 1 ]. While sleep itself is not essential for the nocturnal generation of melatonin, it is unquestionably crucial that the night-time hours be completely dark. For instance, sleep loss alone does not stop the nocturnal, circadian secretion and manufacture of melatonin [ 9 ]. Regardless of the reason for sleep loss at night, the nocturnal, circadian melatonin signal should be unaffected as long as the person is exposed to complete darkness. The term "biological night" refers to the time when melatonin is synthesized and secreted into the bloodstream and has been defined by research on humans under normal, ongoing conditions [ 10 ]. Thus, the initiation of the melatonin surge, a concomitant rise in sleep propensity, and a reduction in core body temperature marks the beginning of this biological night; the opposite occurs at the end of the biological night and sleeps [ 10 ]. The melatonin-producing pineal gland may also interpret electromagnetic radiation as light. As a result, electromagnetic radiation emitted from digital gadgets may also cause melatonin production to be hindered, which disrupts sleep [ 1 ].

Cardiovascular system

It is asserted that sedentary behavior raises the likelihood of obesity, high-density lipoprotein (HDL) dysfunction, and hypertension, the three main cardiovascular morbidity risk factors [ 1 ].

Reduced sleep, physical inactivity, and exposure to excessive advertisements on various media have a detrimental impact on the dietary habits of the younger generation; also contributing to the correlation between screen time and obesity [ 11 ]. As far as digital media is concerned, watching television before one's bedtime is closely linked to the development of obesity during childhood and adolescence, which can further result in cardiometabolic risk [ 12 ]. In typical circumstances, a rise in satiety sensations is usually followed by an increase in plasma glucose; however, in the study, before eating, there was an increase in plasma glucose that peaked higher than it would have addressed. The findings, thus, revealed that video games are closely connected with acute stress (the fight-or-flight response). A release of glucose into the bloodstream seems to be related to this stress reaction [ 13 ].

Blood Pressure

One potential marker of future cardiovascular problems is retinal arteriolar constriction. The results show that children who spend more time outdoors tend to have bigger retinal arterioles than those who spend less time outside [ 14 ].

Cholesterol

Playing video games is the only form of sedentary activity that is associated with a decline in HDL cholesterol in obese teenagers [ 15 , 16 ]. Over three hours of screen usage is linked to a considerable reduction in HDL cholesterol. Mechanisms that explain this relation take into consideration the increased consumption of food advertised extensively, the decrease in food intake regulation during the time on screens, and stillness and loss of movement and physical activity. An example of this is a study that discovered that screen time leads to impairment in satiety signals through the system of mental reward, thereby directly affecting food intake [ 1 ]. 

Stress regulation

Sympathetic Arousal

Cardiovascular issues may be at risk due to chronic sympathetic arousal. Greater sympathetic arousal was observed in teenagers and youngsters who engaged in addictive online behavior. High arousal was suggested as one of the potential contributing factors to sleep disruption by researchers [ 1 ].

For pediatric investigations, cortisol, a hormone produced by the hypothalamic-pituitary-adrenal (HPA) axis, is a stress biomarker. Poor performance is linked to both low and elevated cortisol levels. During the nighttime, the cortisol levels are typically at their lowest. The rate of cortisol increases as the waking hours approach and undergoes a sharp spike after waking up [ 1 ]. As much as three hours per day of media usage by school-aged youngsters results in a lessened cortisol surge an hour after waking up which is detrimental [ 17 ]. Children who engage with digital media for less than three hours each day or have no digital media footprint show a regular increase in morning cortisol levels.

Insulin and Diabetes

The islets of Langerhans of the pancreas secrete the hormone insulin, which is vital for controlling metabolism and storing fat. Insulin resistance is a condition that occurs when cells are unable to use insulin effectively. It makes an essential contribution to the pathophysiology of diabetes and increases the risk of developing cardiovascular disease. According to some research, watching television, playing video games, or using the computer for more than an additional hour a day can result in a 5% reduction in insulin sensitivity. Other research linked as little as two hours of screen time per day to aberrant insulin levels [ 1 ].

Constantly staring at a PC screen can result in headaches, eye strain, impaired vision, dry eyes, and irritation. Such symptoms may be brought on by glare, inadequate illumination, or a wrong viewing angle. According to research, being in an outside environment stimulates the release of dopamine from the retina, which prevents myopia, or near-sightedness, from developing [ 18 ]. As a result, children who spend fewer hours outside have a higher chance of developing the same. Additionally, spending time outside can lessen and largely eliminate the factors that contribute to the development of myopia, such as prolonged close work or screen viewing. The participating young subjects who have been playing video games for more than 30 minutes nearly on a day-to-day basis reported headaches, vertigo, and eye strain. The dominant eye primarily experienced transient diplopia and refractive problems (such as short-sightedness), ultimately leading to vision loss [ 1 ].

Orthopedics

Sedentary habits, or sitting activities that don't involve exercise, can have a significant impact on one's joints and bones. It is argued that screen usage, especially on small-screen mobile devices, affects posture and causes musculoskeletal strain and pain sensations. Similar symptoms can be brought on by the frequent, repeated wrist and arm movements and head inclination typical of playing video games. Bone mineral density is found to be negatively correlated with boys' video gaming play time. The mineral composition of the femoral and spinal bones is inversely correlated with girls' screen time [ 1 ].

Depression and suicidal behavior

Depression, mainly social media-induced depression is a growing concern, particularly among today’s generation [ 19 ]. Those not aware of the usage of social media effectively can easily get trapped in a pattern of jealousy, envy, self-doubt, and poor self-esteem [ 20 ]. It is well known that sleep disturbance symptoms appear before symptoms of depression and suicidal thoughts. Therefore, it is proposed that a mediating element connecting night-time screen use to depressive symptoms and suicidal thoughts in adolescents is the lack of sleep [ 21 ]. The researchers further note that dependence on smartphones, frequent messaging, and protracted fear about not receiving back messages, particularly before bedtime, are likely associated with mood swings, suicidal thoughts, and self-injury. 

ADHD (attention deficit hyperactivity disorder)

Children in today's society may oftentimes exhibit different symptoms of ADHD, such as inattentiveness, hyperactivity, and impulsivity. This type of conduct is known as ADHD-related behavior and can be connected to one's screen time [ 22 ]. It has also been stated that excessive digital device usage is prevalent among younger children and teenagers who have either been already diagnosed with ADHD or who are regarded to be dealing with attention issues or impulsivity [ 23 ].

Addictive screen time behavior

While a substantial percentage of men seem to exhibit video game addiction, women on the other hand are primarily focused on social networking [ 1 ].

Neuropsychological Effects

Numerous investigations so far have concluded that any form of addiction to the internet causes structural changes in the brain, specifically in its frontal lobe. The ability to filter out irrelevant information and a reduced capacity for coping with demanding and complex tasks are related to such structural alterations. The frontal lobe is majorly concerned with controlling overly assertive and wrong, miscellaneous behaviors, as well as adjusting to environmental change [ 1 ]. Other research has shown that control over one’s emotions, visible discord during the decision-making process, and compulsively repetitive behaviors are linked to damaged white matter. Studies have examined the impact of screen multitasking when continuous attention across media devices becomes a substitute for "real world" behavior [ 4 ]. The anterior cingulate cortex, which is connected to cognitive control of performance and socioemotional regulation, is found to have less grey matter in college students with high multitasking scores. Poor performances have been recorded in college students who have been switching between tasks, working memory, and filtering through tests [ 24 ]. Another study on the same group found links between less grey matter and poorer conflict detection of conflict, increased neuroticism and impulsivity, poorer control over behavior that are goal-oriented, and increased conduct motivated by sensations [ 1 ].

Behavioral and Societal Aspects of Social Media Usage in Digital Spaces

This cohort is characterized by increased attentional lapses that have been self-reported regularly, a non-deliberate occasion of mental wandering, which is consistent with the result that grey matter decreases in heavy media multitasking young adults [ 25 ]. The main symptom of ADHD in university students is non-deliberate mind-wandering, which is linked to decreased levels of mindfulness and a higher prevalence of non-adaptive or negative thought patterns. Teenagers who are hooked to the internet and exhibit stronger depressive, hostile and ADHD-related symptoms are found to have non-adaptive/negative thinking patterns [ 26 ]. Therefore, it would seem that media addiction is correlated with increased mental wandering. Individuals who multitask frequently and are screen addicts were also discovered to have lower levels of social support and peer support or attachment to their families and relations. As a result, their level of life contentment is lowered. Teenagers are moving away from face-to-face connection, which is limiting offline social support even though it has increasingly been linked to positive social well-being [ 27 ]. They are more likely to get caught up in a dangerous cycle of continued usage of the internet and social networking websites in an effort to rekindle to social support that they crave when facing obstacles. However, the guise of support that individuals can receive online aids in sustaining their repetitive Internet usage even more [ 28 ]. On the other side, social support that is unrelated to screens may reduce internet addiction. A lack of societal support and increased mind wandering are likely to facilitate social functioning and raise the likelihood of more profound sadness, loneliness, and isolation, which may further enhance addictive behavior [ 29 , 30 ].

Additionally, it is highlighted that social support, attachment to materialistic or figurative objects, mindfulness of one’s surroundings and the feeling of others, and degree of life satisfaction are all psychological and social aspects that are adversely impacted by compulsive screen use and are essential to an individual's resilience in the face of adversities in life [ 31 ]. Furthermore, behavior resulting in incidents of cyberbullying and the social components of addicted internet use appears to be related [ 1 ]. Women in their early adolescence and early years of adulthood are more likely than men to spend more time on social media, be subjected to higher risks of cyberbullying, and experience detrimental mental health issues, the aforementioned are proving to be consistent with the recent epidemiologic trends illustrating that young females, in particular, are more likely to experience an increase in symptoms of depression, self-harm tendencies, and suicidal thoughts [ 32 ].

With children increasingly using wireless gadgets, worries about their susceptibility to radio-frequency electromagnetic radiation (RF-EMR) fields are growing. Kids' growing neurological systems are thought to be quite susceptible to RF-EMR fields, making them possibly more vulnerable. Moreover, compared to the size of their head, more RF-EMR can penetrate their brain tissue because it is better conductive. They will also be exposed to RF fields for more years than grown-ups [ 1 ].

Infertility

Infertility is a common condition that affects 7% of men and 11% of women in the U.S. [ 1 ]. There is a necessity to establish the links between environmental exposures and sperm quality indicators are given that there is evidence of a deterioration in semen quality in recent years [ 33 ]. Exposure to smartphones has been linked to reduced sperm viability and motility. Studies on experimental animals and people examined how RF-EMR also affected male reproductive function. On biological tissue, RF-EMR might have thermal and non-thermal effects both. Reactive oxygen species (ROS) may be produced more frequently as a result of nonthermal interactions, which may cause DNA damage. A little amount of ROS has a crucial functional role in the acrosome response, binding to the oocyte, as well as sperm capacitation. Since phones are frequently kept in pant pockets close to the reproductive organs, thermal impacts potentially raise the temperature of the testes, hampering spermatogenesis and sperm production [ 33 ]. Mobile phones are found to be a potential contributing factor in light of newly discovered evidence of a deterioration in the quality of male sperm. According to the findings of these studies, using a cell phone or a laptop, or a tablet when exposed to RF-EMR increases one's risk of developing cancer as well [ 1 ].

A decline in academic performance

The findings in a cohort study indicate that overall screen time, and the duration spent using a smartphone, are both strongly correlated with the academic stress score and increases the likelihood of abnormal academic stress. One explanation might be the use of cell phones and other electronic devices for homework. This is corroborated by a research study that found that children utilize smartphones and other devices mostly to complete their homework. Hence, the amount of time spent using a device may partly reflect how much schoolwork pupils have to do and the stress that comes with it [ 34 ]. Utilizing electronic devices for social interaction and entertainment may be another factor. More than 30% of teenagers, according to one research, use cell phones and other gadgets for social interaction. Spending a lot of time on social activities and entertainment might interfere with study time, hindering students' academic achievement and raising stress levels [ 35 ]. In the meantime, a bidirectional association has also been established between screen time and academic stress because of the slow progress of studies, which could lead to additional screen time. Furthermore, using a smartphone for social media and amusement might make it difficult for students to concentrate on their work, which could result in unsatisfactory academic results. A rise in academic stress could also eventually be triggered by inferior academic achievements [ 36 ]. The range of digital media devices is expanding rapidly, and improving digital media provides society with a more vibrant and quick-paced digital world. Children and teenagers in particular seem to adapt to modern technologies quickly. But, a growing body of literature associates excessive screen time with physical, psychological, social, and neurological adverse health consequences. Developmental, pornographic exposure and learning effects are additional effects of screen time that require further in-depth analysis and are beyond the scope of this review article. Until very recently, the majority of the literature on children and adolescents use of digital media focused on TV and computers. However, as people seem to utilize mobiles increasingly, studies are shifting their focus accordingly [ 1 ]. Even though the Internet continues to be a powerful and uplifting force in the lives of many, a percentage of users may develop an addiction. Due to their growing online usage and heightened susceptibility to the emergence of addictive behaviors, adolescents are a noteworthy worry in this regard [ 37 ]. Undoubtedly one of the most difficult problems facing the social sciences to this date is the increase in smartphone and social media use. Popular science books and news reports on the psychological effects of social media use are in high demand, and many of these works paint a very ominous picture: social media is often said to have a negative impact on people's lives and societies [ 3 ].

Excessive Internet use has negative effects that are obvious and detrimental, ranging from sleep deprivation, increased depression, and skipping school to family conflict. Comorbid depression, anxiety, ADHD, and other substance-use disorders are widespread. Various markers of individual personality, such as impulsivity, aggressiveness, sensation seeking, family conflicts, as well as inadequate parental supervision, also especially belonging to the male gender have proven to be additional risk factors [ 8 ]. Non-adaptive or negative thought patterns, a lower sense of fulfillment in life, and a propensity for health concerns throughout maturity are several other characteristics that one may notice appearing. The concluding results present that a lack of physical, real-life interaction, extensive multitasking, increased usage of social media websites, and interactive screen time through addictive web interfaces- mostly through the regular usage of video games that require online multiplayer interactions, which do not allow the players to pause the games or exit the rounds- all of these play a significant role in determining the emotional, psychological and physiological impacts on the population. According to research from the Centers for Disease Control and Prevention (Figure  1 ), children aged 8 to 10 spend six hours per day using screens, children aged 11 to 14 spend nine hours, and teenagers aged 15 to 25 spend seven and a half hours per day using screens (including television). The chart below (Figure  2 ) shows screen time recommendations by age, from infants to adults based on the study by the American academy of child and adolescent psychiatry.

This figure has been taken from an open-access journal under a CC-BY license.

Source: American Academy of Child and Adolescent Psychiatry [ 38 ].

Overusing digital screens during one's adolescence and young adulthood may result in their mind relating to outside stimuli rather readily and cause a lack of attention. Internal triggers such as unhelpful or negative thoughts and feelings of lower satisfaction levels regarding one's life can also be accompanied by an onset of health problems in adulthood, such as cardiovascular disease and infertility. It may cause one's stress to increase up to levels that would turn difficult for one to handle. These ailments can result in unhealthy coping mechanisms, which eventually might increase the likelihood of sadness, depression, and anxiety in one's later years. One can successfully deal with difficult life situations if they have a strong sense of personal resilience. Physical fitness, societal support, forms of attachment, the mindfulness towards issues, and the degree of life pleasure, both temporary and permanent, are some of the crucial components of resilience, which is a dynamic psychophysiological construct that can stand jeopardized by excessive screen time and digital footprints. Therefore, it indicates that individuals who use digital media excessively and compulsively have been compromising their ability to build solid psychophysiological foundations, which are essential for the development of resilient people in the future [ 1 ]. Moreover, the COVID-19 pandemic has significantly expanded the use of video conferencing. People of all ages are using video conferencing apps for regular social activities like meetings, birthdays, exercises, and so on due to social distance laws and travel limits. Such video conferencing apps have also made body dysmorphic disorder worsen and are very concerning in the long run. Patients with pre-existing BDD spend too much time and money on a variety of treatments to correct their perceived flaws [ 39 ]. Hence, excessive screen time, be it recreational or non-recreational, can result in a plethora of disadvantages and harm individuals in ways that could perhaps cause irreversible damage to them throughout their entire lifetime. According to numerous studies, time spent on screens irrefutably proves to be more harmful instead of beneficial. With the advancement of technology, it is to be acknowledged that individuals in the contemporary era are extensively involved with the digital world with or without their consent, with regard to their school and university studies or work responsibilities. It is thus necessary for one to recognize the opportunities and obstacles that social media and digital spaces offer and navigate them accordingly. 

Conclusions

This review article studied the relationships between screen time and digital device usage, precisely during the night times, the quality of sleep, anxiety causes, feelings of depression, and issues related to self-esteem, as well as physical effects in individuals. Results also show that exposure to mobile phones has a deleterious impact on the viability and motility of sperm. 

A strategy that would prohibit digital media usage would be ineffective given how crucial it is for one to be involved in digital spaces, specifically social media norms. That being said, in the context of numerous initiatives aimed at addressing the societal, environmental as well as economic factors that support the betterment of one's family and foster resilience in the youth, who could also readily benefit from proven systemic and specifically conducted individual interventions to assist them in navigating through the hurdles brought on by the usage of cell phones and social media, thus, protecting themselves from harm, and further using it in a certain way that maintains their emotional wellbeing above all. However, from the perspective of public health, screen time in general, and the time spent using a smartphone, should be limited in order to lessen and prevent several linked health issues.

The content published in Cureus is the result of clinical experience and/or research by independent individuals or organizations. Cureus is not responsible for the scientific accuracy or reliability of data or conclusions published herein. All content published within Cureus is intended only for educational, research and reference purposes. Additionally, articles published within Cureus should not be deemed a suitable substitute for the advice of a qualified health care professional. Do not disregard or avoid professional medical advice due to content published within Cureus.

The authors have declared that no competing interests exist.

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Research into seldom-heard groups within the Scottish Social Security System

Evidence review setting out the current seldom-heard groups across the Scottish social security system and the barriers they face to accessing their entitlements.

5. Enablers to claiming benefits

In the previous section, we identified psychological, learning and compliance barriers to take-up of social security benefits that acted to marginalise, often already marginalised, people. In this section we report on the evidence for approaches and strategies that help to overcome these barriers to claiming and, therefore, increase take-up rates. Examples of approaches being used to reduce barriers to claiming for marginalised groups are included in Appendix D .

5.1. What works to reduce psychological barriers to claiming benefits?

While this review found no formal evaluations of strategies or interventions to reduce the psychological costs of claiming benefits, the literature offers several suggestions from primary research with seldom heard groups for ways to reduce barriers to claiming.

5.1.1. Positive messaging

The first suggestion to reduce psychological barriers is to change the tone of political and media narratives about claiming benefits to help reduce the stigma associated with claiming [16,19,52] . A study exploring how disability benefits could reduce poverty in Scotland suggested that stigma and prejudice around claiming Adult Disability Payment could be reduced by messaging to “re-establish the fact Disability Assistance is for additional costs of living incurred by disabled people” [49] .

The Scottish Government has committed to delivering devolved benefits in keeping with its values of dignity, fairness and respect [78] . There is evidence that this commitment is inspiring hope of meaningful culture change in Social Security Scotland among disabled people and disability support organisations [41,49] . In the Trussell Trust’s study of drivers of food bank use among disabled people, a participant reported that the inclusion of people with a wide range of disabilities in a television advertisement for Adult Disability Payment had made them feel more validated as a disabled person entitled to support from the social security system [41] . However, there is a risk of reputational damage and of damage to claimants’ trust in the benefits system if real change fails to occur [41,49] . If stigmatising beliefs about and prejudice towards benefit claimants are to be eliminated from Scotland’s social security system, it is vital that culture change is embedded across the system through ongoing staff training and development [41,49] .

5.1.2. Sensitive messaging

Secondly, a need is identified for sensitive and careful messaging to avoid further stigmatisation of people from already marginalised groups (see Appendix D ). Seldom Heard Voices Research participants stressed the need for empathetic communications to avoid further marginalising vulnerable people. Age Scotland highlighted the risk of inadvertently stigmatising people marginalised from the labour market in messaging that characterises benefits as entitlements earned in return for paid work [52] . Staff from organisations supporting minoritised ethnic communities, who took part in a qualitative study on the intersecting impacts of mental ill-health and money problems on the financial wellbeing of people from ethnic minorities, identified the importance of messaging that responds to the ways in which concepts and the language used to describe them can differ across cultures [50] . This study also highlighted the importance of involving people from minoritised ethnic communities in delivering communications around benefits.

5.1.3. Culturally aware support services

Finally, there is evidence of the importance of providing culturally adapted support services that are aware of and responsive to the needs of diverse communities [50,61] . For example, Evans et al stress the likely importance of services staffed by people who properly understand the range of cultural sensitivities around talking about issues such as money worries and mental health [50] .

5.2. What works to reduce learning barriers to claiming benefits?

5.2.1. joined-up approaches.

As reported in Section 4 above, benefit take-up can be negatively impacted by incorrect assumptions that information is routinely shared between, or within, agencies. Data sharing between national and local government departments that allows data-led targeting and targeted take-up campaigns have been shown to be effective in helping local authorities to increase benefit take-up rates [19,79] . The older-people’s advocacy organisation Independent Age cites as an example of good practice the ‘Tell Us Once’ bereavement service, which shares information between government departments including council services, the DWP and the HMRC [80] . This suggests that the Tell Us Once approach could be usefully replicated to increase take-up of Pension Credit and Council Tax reductions [80] . Collecting information from welfare advice and advocacy organisations on ‘pressure points’ in the benefits application system are also being used to improve take-up [76] (see Appendix D for more detail).

5.2.2. Awareness-raising

Several sources identify the effectiveness of maximising awareness of benefits by disseminating information and advice through a wide range of contact opportunities; for example, through healthcare professionals, housing associations, emergency services, and care providers (see enablers tables in Appendix D for examples). There is evidence to suggest that taking advice and information to where people are may be particularly effective in increasing take-up of benefits for marginalised groups [81,82] . For example, locating advice services in general practice. Further, following an advertising campaign promoting the Scottish Best Start Foods payment in 2000 convenience stores across Scotland there was a 5 percentage point increase in take-up [39] suggesting that promoting payments in places where people go could have a positive impact on take-up.

Already known and trusted professionals would be well placed to help people check and claim their entitlements [29] . NHS England’s Making Every Contact Count ( MECC ) approach, where public-facing workers use routine contacts as opportunities for health and wellbeing conversations, is an example of strategic awareness raising that may prove effective in other contexts. There is early evidence that the MECC approach can have positive impacts for seldom heard groups and staff who support them [83] . Evan’s et al highlight the importance of public services that are encouraged and enabled to go beyond providing their core business (e.g. health, education, policing) to address wider determinants of poor outcomes among minority ethnic communities, including insufficient income [50] . Integrating services that provide support and advice on applying for benefits into general practice has been found to increase take-up [84,85,85,86,87] (see Appendix D for further details).

Targeted awareness-raising delivered by trusted organisations has also been shown to be effective in increasing benefit take-up among marginalised groups [29,34,41,69,85] . Public awareness-raising campaigns can also succeed in increasing take-up of benefits (e.g., Pension Credit campaign) [16] . The Joseph Rowntree Foundation’s analysis of underclaiming of benefits among people on low incomes suggests that a Universal Credit take-up campaign that emphasises the value of passported benefits (e.g., access to free school meals, free prescriptions and cost of living payments) may be successful in increasing take-up rates [88] . However, to be successful in the longer-term, campaigns need to receive long-term funding [67] . As part of its Benefit Take-Up Strategy, the Scottish Government has funded information campaigns to raise awareness of the devolved benefts [39] . There is some evidence that these campaigns were followed by increased take-up of some benefits. For example, following national and targeted marketing to raise awareness of extended eligibility for children up to age 16, take-up rates of the Scottish Child Payment for children aged under 6 increased by 8 percentage points between the years 2021/22 and 2022/23 [39] .The increase in take-up rates for younger children might, in part, be explained by increased awareness of the payment arising from the wider marketing campaign.

5.2.3. Accessible, accurate and timely information and support

While delivering information through a wide range of sources is likely to increase awareness of entitlements, it is equally important that information received is accurate and up to date. Research with members of marginalised groups identified the importance of trained benefit staff who could provide information on benefit changes and how benefits interact [6] . Qualitative research with people supporting minoritised ethnic communities identified the role of trained advice workers in countering ‘fake news’ and misinformation about benefit entitlements that can spread through communities [50] . Making information about benefits fully accessible requires considerations of both format and language. Participants in the Seldom Heard Voices Research programme highlighted the importance of providing information in a range of formats [6] . Accessibility of information could also be improved by providing ‘one-stop-shops’ for advice and benefit checks [16,41,50,89] . In their evidence to the Scottish Parliament Social Security Committee on Benefit Take-up, One Parent Families Scotland recommended informing people of their potential benefit entitlements at “important trigger points”, for example, when registering a birth, or leaving a relationship [90] . Ensuring that information is provided at the earliest opportunity could increase the likelihood of a claim being made.

5.3. What works to reduce compliance barriers to claiming benefits?

5.3.1. simplified application processes.

As discussed in Section 4, there is evidence that the simplification of benefit application processes would improve take-up of benefits. The introduction of automatic enrolment for Scotland’s Five Family Payments (see Appendix D ) is an example of a streamlined application process that is likely to positively impact benefit take-up among families. Increased automation of Scottish Child Payment processing has resulted in reduced payment delays [39] . Following the introduction of automated payments for Scotland’s Best Start Grant School Age Payment, take-up rates increased by 20 percentage points [39] .

Offering a range of application modes may also improve take-up [19,29,41,50,76] . There is early evidence that the provision of an online application form for Scotland’s Adult Disability Payment is reducing barriers to take-up among some disabled people [41] . However, as reported above, digital exclusion among many marginalised groups means it is important that there is provision of a range of application methods.

5.3.2. Support to make a claim

Providing support to make a claim has been widely identified as vital for increasing take-up [6,6,29,30,37,41,50,53,91] . Research on disability benefit take-up conducted on behalf of the Trussell Trust found that, for many disabled people, receiving support with an application played a fundamental role in the success of their claim [41] . In evidence to the Social Security Committee, Spicker identified ‘human contact’ as one of the most effective ways of increasing benefit take-up [11] . Social Security Scotland provides an independent advocacy service for disabled applicants. However, while welcomed by disabled people there is qualitative evidence that levels of awareness about the advocacy service are low and better promotion of the service is required to ensure that people receive the support to which they are entitled [41] .

A need has also been identified for frontline staff to be trained to provide culturally aware support that recognises and responds to the barriers to take-up experienced by different marginalised groups [50,61] . An interesting example is provided by the CEMVO who identified cultural barriers to take-up of Scotland’s Funeral Support Payment for communities who are already marginalised from the benefits system and/or who require burial to take place very shortly after death [61] . The CEMVO suggest that frontline staff focus on raising awareness of Funeral Support Payments in these communities and are trained in cultural and religious practices related to funerals [61] .

5.3.3. Increased benefit values and extended eligibility

Increasing the sufficiency of benefits is highly likely to increase take-up, firstly, by reducing the need for a complex array of support (e.g., discretionary funds, crisis loans, and social tariffs) and, secondly, by increasing the utility of claiming [17,18] . There is evidence that people are missing out on passported benefits by not claiming the small amount of Universal Credit to which they are entitled [40] . Extending eligibility to currently ineligible groups (for example, by removing the bedroom tax, two-child policy and benefit cap) would also improve benefit take-up among the most marginalised groups (including survivors of abuse, kinship carers and large families) [35,65,92,93] . While extending eligibility through benefit reform is a long-term solution, there are more immediate actions that could be taken. For example, in the Dying in Poverty report, Marie Curie suggest that local authorities should consider fast-tracking people at the end of life through Scotland’s Scheme of Assistance and extending eligibility for Winter Heating Assistance to the terminally ill [32] .

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